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###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:MungeSumstats.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings MungeSumstats_1.2.4.tar.gz
###
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##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.14-bioc/meat/MungeSumstats.Rcheck’
* using R version 4.1.3 (2022-03-10)
* using platform: x86_64-apple-darwin17.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘MungeSumstats/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘MungeSumstats’ version ‘1.2.4’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘MungeSumstats’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                    user system elapsed
get_genome_builds 90.218  5.404  95.877
format_sumstats   52.827  3.351  56.434
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: OK

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###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL MungeSumstats
###
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* installing to library ‘/Library/Frameworks/R.framework/Versions/4.1/Resources/library’
* installing *source* package ‘MungeSumstats’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (MungeSumstats)

R version 4.1.3 (2022-03-10) -- "One Push-Up"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(testthat)
> library(MungeSumstats)
> 
> test_check("MungeSumstats")
Collecting metadata from Open GWAS.
Filtering metadata by substring criteria.
Found 3 GWAS datasets matching search criteria across:
   - 3 trait(s)
   - 1 population(s)
   - 2 category(ies)
   - 2 subcategory(ies)
   - 2 publication(s)
   - 2 consortia(ium)
   - 1 genome build(s)
Collecting metadata from Open GWAS.
Filtering metadata by substring criteria.
Filtering metadata by sample/case/control/SNP size criteria.
Excluding sample/case/control size with NAs.
Found 3 GWAS datasets matching search criteria across:
   - 3 trait(s)
   - 1 population(s)
   - 2 category(ies)
   - 2 subcategory(ies)
   - 2 publication(s)
   - 2 consortia(ium)
   - 1 genome build(s)
Collecting metadata from Open GWAS.
Filtering metadata by substring criteria.
Found 28 GWAS datasets matching search criteria across:
   - 26 trait(s)
   - 1 population(s)
   - 2 category(ies)
   - 2 subcategory(ies)
   - 3 publication(s)
   - 5 consortia(ium)
   - 1 genome build(s)
Downloading VCF ==> /tmp/RtmpVuXGOH/ieu-a-298.vcf.gz
Downloading with download.file.
trying URL 'https://gwas.mrcieu.ac.uk/files/ieu-a-298/ieu-a-298.vcf.gz'
Content type 'application/gzip' length 234480 bytes (228 KB)
==================================================
downloaded 228 KB

Downloading VCF index ==> https://gwas.mrcieu.ac.uk/files/ieu-a-298/ieu-a-298.vcf.gz.tbi
Downloading with download.file.
trying URL 'https://gwas.mrcieu.ac.uk/files/ieu-a-298/ieu-a-298.vcf.gz.tbi'
Content type 'application/gzip' length 37803 bytes (36 KB)
==================================================
downloaded 36 KB

Processing 1 datasets from Open GWAS.

========== Processing dataset : a-fake-id ==========

Downloading VCF ==> /tmp/RtmpVuXGOH/a-fake-id.vcf.gz
Downloading with download.file.
trying URL 'https://gwas.mrcieu.ac.uk/files/a-fake-id/a-fake-id.vcf.gz'
Processing 1 datasets from Open GWAS.

========== Processing dataset : ieu-a-298 ==========

Downloading VCF ==> /tmp/RtmpVuXGOH/ieu-a-298.vcf.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2838be87d5.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e281378347f
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A0	A1	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2838be87d5.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2840e79273.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e281378347f
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2840e79273.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2837ef26da.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e281bf0380a
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A2	A1	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
Loading reference genome data.
There are 47 SNPs where A1 doesn't match the reference genome.
These will be flipped with their effect columns.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Warning: When method is an integer, must be >0.
67 SNPs (72%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2837ef26da.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  G  A 0.63060 -0.017 0.003 2.359e-10
3: rs34305371   1 72733610  G  A 0.91231 -0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2847ec075f.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e281bf0380a
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
There are 46 SNPs where A1 doesn't match the reference genome.
These will be flipped with their effect columns.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Warning: When method is an integer, must be >0.
67 SNPs (72%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2847ec075f.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  G  A 0.63060 -0.017 0.003 2.359e-10
3: rs34305371   1 72733610  G  A 0.91231 -0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e283a395785.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2827474da0
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Loading reference genome data.
1 SNPs are non-biallelic. These will be removed.
Writing in tabular format ==> /tmp/RtmpVuXGOH/snp_bi_allelic.tsv.gz
Warning: When method is an integer, must be >0.
46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e283a395785.tsv.gz
Summary statistics report:
   - 92 rows (98.9% of original 93 rows)
   - 92 unique variants
   - 69 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e287d7a19fb.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2827474da0
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Loading reference genome data.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e287d7a19fb.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e284543d589.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2877314b41
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Ensuring parameters comply with LDSC format.
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
1 SNP IDs are not correctly formatted. These will be corrected from the reference genome.
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
There are 46 SNPs where A1 doesn't match the reference genome.
These will be flipped with their effect columns.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Computing Z-score from P using formula: `sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE)`
Assigning N=1001 for all SNPs.
67 SNPs (72%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e284543d589.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P IMPUTATION_SNP
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08             NA
2: rs11210860   1 43982527  G  A 0.63060 -0.017 0.003 2.359e-10             NA
3: rs34305371   1 72733610  G  A 0.91231 -0.035 0.005 3.762e-14             NA
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08             NA
   flipped         Z IMPUTATION_z_score    N
1:      NA  5.630777               TRUE 1001
2:    TRUE -6.335939               TRUE 1001
3:    TRUE -7.568968               TRUE 1001
4:      NA -5.630488               TRUE 1001
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285462332a.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28769d598c
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	N_CON	N_CAS	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
There are 46 SNPs where A1 doesn't match the reference genome.
These will be flipped with their effect columns.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Computing effective sample size using the LDSC method:
 Neff = (N_CAS+N_CON) * (N_CAS/(N_CAS+N_CON)) / mean((N_CAS/(N_CAS+N_CON))[(N_CAS+N_CON)==max(N_CAS+N_CON)]))
Computing sample size using the sum method:
 N = N_CAS + N_CON
Computing effective sample size using the GIANT method:
 Neff = 2 / (1/N_CAS + 1/N_CON)
Computing effective sample size using the METAL method:
 Neff = 4 / (1/N_CAS + 1/N_CON)
67 SNPs (72%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285462332a.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P N_CON N_CAS
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08   100   120
2: rs11210860   1 43982527  G  A 0.63060 -0.017 0.003 2.359e-10   100   120
3: rs34305371   1 72733610  G  A 0.91231 -0.035 0.005 3.762e-14   100   120
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08   100   120
   Neff_ldsc   N Neff_giant Neff_metal
1:       220 220        109        218
2:       220 220        109        218
3:       220 220        109        218
4:       220 220        109        218
Returning path to saved data.
Reading header.
Tabular format detected.
Reading header.
Tabular format detected.
Reading header.
Tabular format detected.
Reading header.
Reading header.
Tabular format detected.
Importing tabular file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/MungeSumstats/extdata/eduAttainOkbay.txt
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Computing Z-score from P using formula: `sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE)`


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e284bd171ee.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e284118ee7d
Standardising column headers.
First line of summary statistics file: 
MarkerName	EAF	Beta	SE	Pval	CHR_BP_A2_A1	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column.
Column CHR_BP_A2_A1 has been separated into the columns CHR, BP, A2, A1
Standardising column headers.
First line of summary statistics file: 
SNP	FRQ	BETA	SE	P	CHR	BP	A2	A1	
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e284bd171ee.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28772140f1.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e284118ee7d
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28772140f1.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e283cbb6a8b.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28666434a1
Standardising column headers.
First line of summary statistics file: 
MarkerName	EAF	Beta	SE	Pval	CHR_BP_A2_A1	CHR_BP_A2_A1_2	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column.
Warning: Multiple columns in the sumstats file seem to relate to Chromosome:Base Pair position:A2:A1.
The column CHR_BP_A2_A1_2 will be kept whereas the column(s) CHR_BP_A2_A1 will be removed.
If this is not the correct column to keep, please remove all incorrect columns from those listed here before 
running `format_sumstats()`.
Column CHR_BP_A2_A1_2 has been separated into the columns CHR, BP, A2, A1
Standardising column headers.
First line of summary statistics file: 
SNP	FRQ	BETA	SE	P	CHR	BP	A2	A1	
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e283cbb6a8b.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28ccd6b5f.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28666434a1
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28ccd6b5f.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e286b42cbe7.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2812567980
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	EAF	Beta	SE	Pval	alleles	allele	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Warning: Multiple columns in the sumstats file seem to relate to alleles A1>A2.
The column ALLELES will be kept whereas the column(s) ALLELE will be removed.
If this is not the correct column to keep, please remove all incorrect columns from those listed here before 
running `format_sumstats()`.
Column ALLELES has been separated into the columns A1, A2
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e286b42cbe7.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e287804f6c5.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2812567980
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e287804f6c5.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e287f4cdc82.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287a8fedea
Standardising column headers.
First line of summary statistics file: 
MarkerName	A1	A2	EAF	Beta	SE	Pval	CHR_BP	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column.
Column CHR_BP has been separated into the columns CHR, BP
Standardising column headers.
First line of summary statistics file: 
SNP	A1	A2	FRQ	BETA	SE	P	CHR	BP	
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e287f4cdc82.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e286bb14b16.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287a8fedea
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e286bb14b16.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e286d5617df.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2835bc8b30
Standardising column headers.
First line of summary statistics file: 
MarkerName	A1	A2	EAF	Beta	SE	Pval	CHR_BP	CHR_BP_2	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column.
Warning: Multiple columns in the sumstats file seem to relate to Chromosome:Base Pair position.
The column CHR_BP_2 will be kept whereas the column(s) CHR_BP will be removed.
If this is not the correct column to keep, please remove all incorrect columns from those listed here before 
running `format_sumstats()`.
Column CHR_BP_2 has been separated into the columns CHR, BP
Standardising column headers.
First line of summary statistics file: 
SNP	A1	A2	FRQ	BETA	SE	P	CHR	BP	
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e286d5617df.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2838619ea7.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2835bc8b30
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2838619ea7.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28b18c257.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e283e488513
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28b18c257.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e287ac15f0d.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e286ee8dfdd
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e287ac15f0d.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28502a574c.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e284e8cdf8
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28502a574c.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28388a7584.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Saving output messages to:
/tmp/RtmpVuXGOH/MungeSumstats_log_msg.txt
Any runtime errors will be saved to:
/tmp/RtmpVuXGOH/MungeSumstats_log_output.txt
Messages will not be printed to terminal.
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28683f5163.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28a71d9af
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28683f5163.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e287f034f53.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282681428
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 186 rows
   - 93 unique variants
   - 140 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
93 RSIDs are duplicated in the sumstats file. These duplicates will be removed
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e287f034f53.tsv.gz
Summary statistics report:
   - 93 rows (50% of original 186 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e281767bf19.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282681428
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e281767bf19.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2817e42d72.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282681428
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 94 rows
   - 94 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
1 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2817e42d72.tsv.gz
Summary statistics report:
   - 93 rows (98.9% of original 94 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e281e1ffc39.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e285d7e8833
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Filtering effect columns, ensuring none equal 0.
5 SNPs have effect values = 0 and will be removed
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
44 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e281e1ffc39.tsv.gz
Summary statistics report:
   - 88 rows (94.6% of original 93 rows)
   - 88 unique variants
   - 65 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285d0aa697.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e286d6c3cc8
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	FRQ	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs based on FRQ.
38 SNPs are below the FRQ threshold of 0.9 and will be removed.
Writing in tabular format ==> /tmp/RtmpVuXGOH/frq_filter.tsv.gz
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
55 SNPs (100%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285d0aa697.tsv.gz
Summary statistics report:
   - 55 rows (59.1% of original 93 rows)
   - 55 unique variants
   - 41 genome-wide significant variants (P<5e-8)
   - 16 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     EAF   BETA    SE         P      FRQ
1: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10 1.863269
2: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14 1.169733
3:  rs1008078   1 91189731  T  C 0.37310 -0.016 0.003 6.005e-10 1.401423
4: rs61787263   1 98618714  T  C 0.76120  0.016 0.003 5.391e-08 1.873332
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2838b7db76.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e286d6c3cc8
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	FRQ	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs based on FRQ.
38 SNPs are below the FRQ threshold of 0.9 and will be removed.
Writing in tabular format ==> /tmp/RtmpVuXGOH/frq_filter.tsv.gz
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
55 SNPs (100%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=FALSE, the FRQ column will be renamed MAJOR_ALLELE_FRQ to differentiate the values from 
minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2838b7db76.tsv.gz
Summary statistics report:
   - 55 rows (59.1% of original 93 rows)
   - 55 unique variants
   - 41 genome-wide significant variants (P<5e-8)
   - 16 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     EAF   BETA    SE         P
1: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
2: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
3:  rs1008078   1 91189731  T  C 0.37310 -0.016 0.003 6.005e-10
4: rs61787263   1 98618714  T  C 0.76120  0.016 0.003 5.391e-08
   MAJOR_ALLELE_FRQ
1:         1.863269
2:         1.169733
3:         1.401423
4:         1.873332
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285831e9e3.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2866d5b453
Standardising column headers.
First line of summary statistics file: 
SNP	CHR	BP	A1	A2	FRQ	BETA	SE	P	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285831e9e3.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2816e6cde.tsv
Converting full summary stats file to tabix format for fast querying...
Reading header.
Ensuring file is bgzipped.
Tabix-indexing file.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e282ed65409.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287b864fa2
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	INFO	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs based on INFO score.
38 SNPs are below the INFO threshold of 0.9 and will be removed.
Writing in tabular format ==> /tmp/RtmpVuXGOH/info_filter.tsv.gz
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
28 SNPs (50.9%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e282ed65409.tsv.gz
Summary statistics report:
   - 55 rows (59.1% of original 93 rows)
   - 55 unique variants
   - 41 genome-wide significant variants (P<5e-8)
   - 16 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P     INFO
1: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10 1.863269
2: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14 1.169733
3:  rs1008078   1 91189731  T  C 0.37310 -0.016 0.003 6.005e-10 1.401423
4: rs61787263   1 98618714  T  C 0.76120  0.016 0.003 5.391e-08 1.873332
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285374817e.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2843d4fa2c
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285374817e.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2814e38e30.tsv.gz
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2814e38e30.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e281fd52a1.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2850f0d6e2
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Performing data liftover from GRCh37 to GRCh38.
Using existing chain file.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e281fd52a1.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8430543  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43516856  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72267927  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72296486  T  C 0.23690 -0.017 0.003 1.797e-08
   IMPUTATION_gen_build
1:                 TRUE
2:                 TRUE
3:                 TRUE
4:                 TRUE
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2855d70f4d.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e281fd52a1.tsv.gz
Standardising column headers.
First line of summary statistics file: 
SNP	CHR	BP	A1	A2	FRQ	BETA	SE	P	IMPUTATION_gen_build	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Performing data liftover from GRCh38 to GRCh37.
Using existing chain file.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2855d70f4d.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
   IMPUTATION_GEN_BUILD IMPUTATION_gen_build
1:                 TRUE                 TRUE
2:                 TRUE                 TRUE
3:                 TRUE                 TRUE
4:                 TRUE                 TRUE
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28567c6de1.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2850f0d6e2
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28567c6de1.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2848f951ab.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e285e9fbc25
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 92 unique variants
   - 69 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
WARNING: 1 rows in sumstats file are missing data and will be removed.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2848f951ab.tsv.gz
Summary statistics report:
   - 92 rows (98.9% of original 93 rows)
   - 92 unique variants
   - 69 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:  rs12646808   4  3249828  T  C 0.64180  0.016 0.003 4.002e-08
2:    rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
3: rs117468730  16 10205467  A  G 0.02425 -0.049 0.009 1.242e-07
4:  rs76076331   2 10977585  T  C 0.09328  0.020 0.004 3.632e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e281695d231.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e285e9fbc25
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e281695d231.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:  rs12646808   4  3249828  T  C 0.64180  0.016 0.003 4.002e-08
2:    rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
3: rs117468730  16 10205467  A  G 0.02425 -0.049 0.009 1.242e-07
4:  rs76076331   2 10977585  T  C 0.09328  0.020 0.004 3.632e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285cbf2147.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e284fdde0
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
1 SNPs found with multiple RSIDs on one row, the first will be taken. If you would rather remove these SNPs set
`remove_multi_rs_snp=TRUE`.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285cbf2147.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
   convert_multi_rs_SNP
1:                   NA
2:                   NA
3:                   NA
4:                   NA
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e281a79726f.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e284fdde0
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e281a79726f.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28b5bf74f.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287b6f9d48
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 92 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Writing in tabular format ==> /tmp/RtmpVuXGOH/snp_multi_rs_one_row.tsv.gz
1 SNPs found with multiple RSIDs on one row, these will be removed. If you would rather take the first RS ID set
`remove_multi_rs_snp`=FALSE
Checking SNP RSIDs.
1 SNP IDs are not correctly formatted. These will be corrected from the reference genome.
Writing in tabular format ==> /tmp/RtmpVuXGOH/snp_not_found_from_chr_bp.tsv.gz
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
There are 43 SNPs where A1 doesn't match the reference genome.
These will be flipped with their effect columns.
Checking for missing data.
WARNING: 1 rows in sumstats file are missing data and will be removed.
Writing in tabular format ==> /tmp/RtmpVuXGOH/missing_data.tsv.gz
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
1 RSIDs are duplicated in the sumstats file. These duplicates will be removed
Writing in tabular format ==> /tmp/RtmpVuXGOH/dup_snp_id.tsv.gz
Checking for SNPs with duplicated base-pair positions.
1 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Writing in tabular format ==> /tmp/RtmpVuXGOH/dup_base_pair_position.tsv.gz
Filtering SNPs, ensuring SE>0.
1 SNPs have SE values <= 0 and will be removed
Writing in tabular format ==> /tmp/RtmpVuXGOH/se_neg.tsv.gz
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for strand ambiguous SNPs.
8 SNPs are strand-ambiguous alleles including 4 A/T and 4 C/G ambiguous SNPs. These will be removed
Writing in tabular format ==> /tmp/RtmpVuXGOH/snp_strand_ambiguous.tsv.gz
Checking for bi-allelic SNPs.
Warning: When method is an integer, must be >0.
54 SNPs (68.4%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28b5bf74f.tsv.gz
Summary statistics report:
   - 79 rows (84.9% of original 93 rows)
   - 79 unique variants
   - 57 genome-wide significant variants (P<5e-8)
   - 18 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P IMPUTATION_SNP
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08             NA
2: rs34305371   1 72733610  G  A 0.91231 -0.035 0.005 3.762e-14             NA
3:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08             NA
4:  rs1008078   1 91189731  C  T 0.62690  0.016 0.003 6.005e-10             NA
   flipped
1:      NA
2:    TRUE
3:      NA
4:    TRUE
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e284120093c.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e288f3d8d3
Standardising column headers.
First line of summary statistics file: 
chromosome	rs_id	markername	position_hg18	Effect_allele	Other_allele	EAF_HapMapCEU	N_SMK	Effect_SMK	StdErr_SMK	P_value_SMK	N_NONSMK	Effect_NonSMK	StdErr_NonSMK	P_value_NonSMK	
Summary statistics report:
   - 5 rows
   - 5 unique variants
   - 1 chromosomes
Checking for multi-GWAS.
WARNING: Multiple traits found in sumstats file only one of which can be analysed: 
SMK, NONSMK
Standardising column headers.
First line of summary statistics file: 
CHR	SNP	MARKERNAME	POSITION_HG18	A2	A1	EAF_HAPMAPCEU	N	EFFECT	STDERR	P_VALUE	N_NONSMK	EFFECT_NONSMK	STDERR_NONSMK	P_VALUE_NONSMK	
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
1 SNP IDs are not correctly formatted and will be removed.
Checking for merged allele column.
Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column.
Column MARKERNAME has been separated into the columns CHR, BP
Standardising column headers.
First line of summary statistics file: 
CHR	SNP	POSITION_HG18	A2	A1	EAF_HAPMAPCEU	N	BETA	STDERR	P	N_NONSMK	EFFECT_NONSMK	STDERR_NONSMK	P_VALUE_NONSMK	BP	
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Ensuring that the N column is all integers.
The sumstats N column is not all integers, this could effect downstream analysis. These will be converted to integers.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Ensuring all SNPs have N<5 std dev above mean.
Making X/Y CHR uppercase.
N already exists within sumstats_dt.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e284120093c.tsv.gz
Summary statistics report:
   - 4 rows (80% of original 5 rows)
   - 4 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
         SNP  CHR        BP A1 A2 POSITION_HG18 EAF_HAPMAPCEU     N    BETA
1: rs1000085 chr1  66630503  G  C      66630503        0.1667 38761  0.0053
2: rs1000075 chr1  94939420  C  T      94939420        0.3583 38959 -0.0013
3: rs1000073 chr1 155522020  G  A     155522020        0.3136 36335  0.0046
4: rs1000050 chr1 161003087  C  T     161003087        0.9000 36257  0.0001
   STDERR      P N_NONSMK EFFECT_NONSMK STDERR_NONSMK P_VALUE_NONSMK
1: 0.0095 0.5746   147259       -0.0034        0.0052         0.5157
2: 0.0082 0.8687   147567       -0.0043        0.0044         0.3259
3: 0.0083 0.5812   126780        0.0038        0.0045         0.3979
4: 0.0109 0.9931   127514        0.0058        0.0059         0.3307
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e286cfaf584.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e285759e88
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	N	N_fixed	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Ensuring that the N column is all integers.
The sumstats N column is not all integers, this could effect downstream analysis. These will be converted to integers.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
N already exists within sumstats_dt.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e286cfaf584.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P N N_FIXED
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08 5       5
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10 1       1
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14 1       1
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08 7       7
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2834b0db6a.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2810a2de4e
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	N	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
1 SNPs have N values 5 standard deviations above the mean and will be removed
Writing in tabular format ==> /tmp/RtmpVuXGOH/n_large.tsv.gz
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
N already exists within sumstats_dt.
47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2834b0db6a.tsv.gz
Summary statistics report:
   - 92 rows (98.9% of original 93 rows)
   - 92 unique variants
   - 69 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P N
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08 3
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10 5
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14 3
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08 3
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28567a816e.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2810a2de4e
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	N	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
1 SNPs have N values 5 standard deviations above the mean and will be removed
Writing in tabular format ==> /tmp/RtmpVuXGOH/n_large.tsv.gz
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
N already exists within sumstats_dt.
47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28567a816e.tsv.gz
Summary statistics report:
   - 92 rows (98.9% of original 93 rows)
   - 92 unique variants
   - 69 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P N
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08 3
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10 5
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14 3
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08 3
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28a5fb82c.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2810a2de4e
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	N	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
The sumstats N column is not all integers, this could effect downstream analysis.These will NOT be converted to integers.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
1 SNPs have N values 5 standard deviations above the mean and will be removed
Writing in tabular format ==> /tmp/RtmpVuXGOH/n_large.tsv.gz
Removing rows where is.na(N)
0 SNPs have N values that are NA and will be removed.
Writing in tabular format ==> /tmp/RtmpVuXGOH/n_null.tsv.gz
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
N already exists within sumstats_dt.
47 SNPs (51.1%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28a5fb82c.tsv.gz
Summary statistics report:
   - 92 rows (98.9% of original 93 rows)
   - 92 unique variants
   - 69 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P N
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08 3
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10 5
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14 3
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08 3
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2836d92774.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287a44bd12
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
WARNING: No A2 column found in the data, multi-allelic can't not be accurately chosen (as any
of the choices could be valid). bi_allelic_filter has been forced to TRUE.
Loading reference genome data.
There is no A1 or A2 allele information column found within the data. It must be inferred from other column information.
Deriving both A1 and A2 from reference genome
WARNING: Inferring the alternative allele (A2) from the reference genome. In some instances, there are more than one
alternative allele. Arbitrarily, only the first will be kept. See column `alt_alleles` in your returned sumstats file
for all alternative alleles.
Writing in tabular format ==> /tmp/RtmpVuXGOH/alleles_not_found_from_snp.tsv.gz
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2836d92774.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P alt_alleles
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08           C
2: rs11210860   1 43982527  G  A 0.36940  0.017 0.003 2.359e-10           A
3: rs34305371   1 72733610  G  A 0.08769  0.035 0.005 3.762e-14           A
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08           C
   IMPUTATION_A1 IMPUTATION_A2
1:          TRUE          TRUE
2:          TRUE          TRUE
3:          TRUE          TRUE
4:          TRUE          TRUE
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e283af4316a.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287a44bd12
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Loading reference genome data.
There is no A1 or A2 allele information column found within the data. It must be inferred from other column information.
One of A1/A2 are missing, allele flipping will be tested
Deriving A1 from reference genome
Writing in tabular format ==> /tmp/RtmpVuXGOH/alleles_not_found_from_snp.tsv.gz
Checking for correct direction of A1 (reference) and A2 (alternative allele).
There are 46 SNPs where A1 doesn't match the reference genome.
These will be flipped with their effect columns.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e283af4316a.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P IMPUTATION_A1
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08          TRUE
2: rs11210860   1 43982527  G  G 0.36940 -0.017 0.003 2.359e-10          TRUE
3: rs34305371   1 72733610  G  G 0.08769 -0.035 0.005 3.762e-14          TRUE
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08          TRUE
   flipped
1:      NA
2:    TRUE
3:    TRUE
4:      NA
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28274a7f15.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287a44bd12
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
WARNING: No A2 column found in the data, multi-allelic can't not be accurately chosen (as any
of the choices could be valid). bi_allelic_filter has been forced to TRUE.
Loading reference genome data.
There is no A1 or A2 allele information column found within the data. It must be inferred from other column information.
One of A1/A2 are missing, allele flipping will be tested
Deriving A2 from reference genome
WARNING: Inferring the alternative allele (A2) from the reference genome. In some instances, there are more than one
alternative allele. Arbitrarily, only the first will be kept. See column `alt_alleles` in your returned sumstats file
for all alternative alleles.
Writing in tabular format ==> /tmp/RtmpVuXGOH/alleles_not_found_from_snp.tsv.gz
Checking for correct direction of A1 (reference) and A2 (alternative allele).
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28274a7f15.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P alt_alleles
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08           C
2: rs11210860   1 43982527  A  A 0.36940  0.017 0.003 2.359e-10           A
3: rs34305371   1 72733610  A  A 0.08769  0.035 0.005 3.762e-14           A
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08           C
   IMPUTATION_A2
1:          TRUE
2:          TRUE
3:          TRUE
4:          TRUE
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28749b126e.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287a44bd12
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
Loading reference genome data.
There are 46 SNPs where A1 doesn't match the reference genome.
These will be flipped with their effect columns.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28749b126e.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  G  A 0.36940 -0.017 0.003 2.359e-10
3: rs34305371   1 72733610  G  A 0.08769 -0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e286510fe0f.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e285cb2e5dc
Standardising column headers.
First line of summary statistics file: 
MarkerName	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column.
Standardising column headers.
First line of summary statistics file: 
SNP	BP	A1	A2	FRQ	BETA	SE	P	
Loading reference genome data.
There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e286510fe0f.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2871d1dcde.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2884ede04
Standardising column headers.
First line of summary statistics file: 
MarkerName	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column.
Standardising column headers.
First line of summary statistics file: 
SNP	A1	A2	FRQ	BETA	SE	P	
Loading reference genome data.
There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information.
Writing in tabular format ==> /tmp/RtmpVuXGOH/chr_bp_not_found_from_snp.tsv.gz
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2871d1dcde.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2842d79d01.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287b4646e1
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
1 SNP IDs are not correctly formatted. These will be corrected from the reference genome.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2842d79d01.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285479621f.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287b4646e1
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285479621f.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e281f9c21c2.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282cce417b
Standardising column headers.
First line of summary statistics file: 
MarkerName	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
1 SNP IDs appear to be made up of chr:bp, these will be replaced by their SNP ID from the reference genome
1 SNP IDs are not correctly formatted and will be removed.
Checking for merged allele column.
Summary statistics file does not have obvious CHR/BP columns. Checking to see if they are joined in another column.
Standardising column headers.
First line of summary statistics file: 
SNP	A1	A2	FRQ	BETA	SE	P	
Loading reference genome data.
There is no Chromosome or Base Pair Position column found within the data. It must be inferred from other column information.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
46 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e281f9c21c2.tsv.gz
Summary statistics report:
   - 92 rows (98.9% of original 93 rows)
   - 92 unique variants
   - 69 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e287cbcc8a4.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28192d0938
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
1 SNP IDs are not correctly formatted. These will be corrected from the reference genome.
1 SNP IDs appear to be made up of chr:bp, these will be replaced by their SNP ID from the reference genome
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e287cbcc8a4.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e283fa6865b.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e285bb84871
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e282ea6722e.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282cce417b
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e282ea6722e.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2859fa35c7.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28ddaeba
Standardising column headers.
First line of summary statistics file: 
CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking for merged allele column.
There is no SNP column found within the data. It must be inferred from other column information.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2859fa35c7.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28443d773e.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287010649c
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
1 SNPs are not on the reference genome. These will be corrected from the reference genome.
Writing in tabular format ==> /tmp/RtmpVuXGOH/snp_not_found_from_chr_bp.tsv.gz
Loading reference genome data.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28443d773e.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285519c103.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287010649c
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Ensuring all SNPs are on the reference genome.
Loading reference genome data.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285519c103.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.
Inferring genome build of 1 sumstats file(s).
ss1
Inferring genome build.
Reading in only the first 50 rows of sumstats.
Reading header.
Tabular format detected.
Importing tabular file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/MungeSumstats/extdata/eduAttainOkbay.txt
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Loading reference genome data.
Loading reference genome data.
Inferred genome build: GRCH37
Time difference of 1.042526 mins
GRCH37: 1 file(s)


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28af6e4ed.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28776cd874
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 23 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
3 SNPs are on chromosomes X, Y, MT and will be removed
Writing in tabular format ==> /tmp/RtmpVuXGOH/chr_excl.tsv.gz
Warning: When method is an integer, must be >0.
45 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28af6e4ed.tsv.gz
Summary statistics report:
   - 90 rows (96.8% of original 93 rows)
   - 90 unique variants
   - 67 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e283acb3060.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28776cd874
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e283acb3060.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e281bc9438c
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e287c75f885
Converting summary statistics to Genomic Ranges.
Converting summary statistics to VRanges.
Writing in VCF format ==> /tmp/RtmpVuXGOH/file12e284ea24d1.vcf.gz
Reading header.
Importing VCF file: /tmp/RtmpVuXGOH/file12e284ea24d1.vcf.gz
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	GWAS	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'GWAS' data column.
1 empty column(s) detected.
Formatting INFO column.
NOTE: All INFO scores are empty. Replacing all with 1.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	FRQ	BETA	SE	P	
0 empty column(s) detected.
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	EBI-a-GCST005647	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'EBI-A-GCST005647' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
INFO column is actually AF, it will be converted.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	ES	SE	LP	AF	ID	P	
Converting summary statistics to Genomic Ranges.
Converting summary statistics to VRanges.
Writing in VCF format ==> /tmp/RtmpVuXGOH/file12e2871d7655e.vcf.gz
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	GWAS	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'GWAS' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	BETA	SE	LP	FRQ	ID	P	


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e281dba744a.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Standardising column headers.
First line of summary statistics file: 
SNP	P	FRQ	BETA	CHR	BP	
Summary statistics report:
   - 5 rows
   - 5 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
5 SNP IDs contain other information in the same column. These will be separated.
Checking for merged allele column.
Column SNP_INFO has been separated into the columns A1, A2
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
3 SNPs (60%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e281dba744a.tsv.gz
Summary statistics report:
   - 5 rows (100% of original 5 rows)
   - 5 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2           P       FRQ      BETA
1: rs140052487   1 54353  C  A 0.037219838 0.3000548 0.8797957
2: rs558796213   1 54564  G  T 0.004382482 0.5848666 0.7068747
3: rs561234294   1 54591  A  G 0.070968402 0.3334671 0.7319726
4:   rs2462492   1 54676  C  T 0.065769040 0.6220120 0.9316344
Returning data directly.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

******::NOTE::******
- Log results will be saved to `tempdir()` by default.
- This means all log data from the run will be deleted upon ending the R session.
- To keep it, change `log_folder` to an actual directory (e.g. log_folder='./').
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2814a54d9e.tsv.gz
Log data to be saved to ==> /tmp/RtmpVuXGOH
Standardising column headers.
First line of summary statistics file: 
SNP	P	FRQ	BETA	CHR	BP	A1	A2	
Summary statistics report:
   - 5 rows
   - 5 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
3 SNPs (60%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2814a54d9e.tsv.gz
Summary statistics report:
   - 5 rows (100% of original 5 rows)
   - 5 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2           P       FRQ      BETA
1: rs140052487   1 54353  C  A 0.037219838 0.3000548 0.8797957
2: rs558796213   1 54564  G  T 0.004382482 0.5848666 0.7068747
3: rs561234294   1 54591  A  G 0.070968402 0.3334671 0.7319726
4:   rs2462492   1 54676  C  T 0.065769040 0.6220120 0.9316344
Returning data directly.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285bd08d5a.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2827ff1551
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e283767374.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e284ab3259
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
There are existing p-values as low as 5e-324 which LDSC/MAGMA may not be able to handle. These will be converted to 0.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e283767374.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28f839bf1.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e284ab3259
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28f839bf1.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28196975c7.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2878551359
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28196975c7.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28320a2e3c.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e286864cde7
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
47 SNPs (50.5%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28320a2e3c.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28275e5cb7.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282fc2f108
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
5 SNPs have SE values <= 0 and will be removed
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
44 SNPs (50%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28275e5cb7.tsv.gz
Summary statistics report:
   - 88 rows (94.6% of original 93 rows)
   - 88 unique variants
   - 65 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28654f44c1.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282a78de5f
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 85 rows
   - 85 unique variants
   - 63 genome-wide significant variants (P<5e-8)
   - 19 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for strand ambiguous SNPs.
Warning: When method is an integer, must be >0.
43 SNPs (50.6%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28654f44c1.tsv.gz
Summary statistics report:
   - 85 rows (100% of original 85 rows)
   - 85 unique variants
   - 63 genome-wide significant variants (P<5e-8)
   - 19 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2874e6c74c.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282a78de5f
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for strand ambiguous SNPs.
8 SNPs are strand-ambiguous alleles including 4 A/T and 4 C/G ambiguous SNPs. These will be removed
Warning: When method is an integer, must be >0.
43 SNPs (50.6%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2874e6c74c.tsv.gz
Summary statistics report:
   - 85 rows (91.4% of original 93 rows)
   - 85 unique variants
   - 63 genome-wide significant variants (P<5e-8)
   - 19 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     FRQ   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28558e2e38.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28697c8a69.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28752ed4b2
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28697c8a69.tsv.gz
Summary statistics report:
   - 93 rows (100% of original 93 rows)
   - 93 unique variants
   - 70 genome-wide significant variants (P<5e-8)
   - 20 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
          SNP CHR       BP A1 A2     EAF   BETA    SE         P
1:   rs301800   1  8490603  T  C 0.17910  0.019 0.003 1.794e-08
2: rs11210860   1 43982527  A  G 0.36940  0.017 0.003 2.359e-10
3: rs34305371   1 72733610  A  G 0.08769  0.035 0.005 3.762e-14
4:  rs2568955   1 72762169  T  C 0.23690 -0.017 0.003 1.797e-08
Returning data directly.
Converting summary statistics to Genomic Ranges.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28327b7ac2.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2848b87072.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2844de71aa.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2867f87338.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28685496db.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2897c3960.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e283a9ad27d.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28a712a9a.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28ba3e9d1.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28364b9e4f.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e281e867062.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2847f5e520.tsv.gz
Reading header.
Importing VCF file: /tmp/RtmpVuXGOH/file12e28c3c4196.vcf
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	EBI-a-GCST005647	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'EBI-A-GCST005647' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
INFO column is actually AF, it will be converted.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	ES	SE	LP	AF	ID	P	
Summary statistics report:
   - 101 rows
   - 101 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Filtering SNPs based on INFO score.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2847f5e520.tsv.gz
Summary statistics report:
   - 99 rows (98% of original 101 rows)
   - 99 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2   INFO    BETA     SE       LP    FRQ
1:  rs58108140   1 10583  G  A 0.1589  0.0312 0.0393 0.369267 0.1589
2:    rs806731   1 30923  G  T 0.7843 -0.0114 0.0353 0.126854 0.7843
3: rs116400033   1 51479  T  A 0.1829  0.0711 0.0370 1.262410 0.1829
4: rs146477069   1 54421  A  G 0.0352 -0.0240 0.0830 0.112102 0.0352
            ID          P
1:  rs58108140 0.42730011
2:    rs806731 0.74669974
3: rs116400033 0.05464998
4: rs146477069 0.77249913
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2835a066b2.tsv.gz
Reading header.
Importing VCF file: /tmp/RtmpVuXGOH/file12e2869d2002.vcf
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	EBI-a-GCST005647	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'EBI-A-GCST005647' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
INFO column is actually AF, it will be converted.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	ES	SE	LP	AF	ID	P	
Summary statistics report:
   - 101 rows
   - 101 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
Loading reference genome data.
There are 1 SNPs where A1 doesn't match the reference genome.
These will be flipped with their effect columns.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Filtering SNPs based on INFO score.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Checking for bi-allelic SNPs.
Warning: When method is an integer, must be >0.
2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2835a066b2.tsv.gz
Summary statistics report:
   - 99 rows (98% of original 101 rows)
   - 99 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2   INFO    BETA     SE       LP    FRQ
1:  rs58108140   1 10583  G  A 0.1589  0.0312 0.0393 0.369267 0.1589
2:    rs806731   1 30923  G  T 0.7843 -0.0114 0.0353 0.126854 0.7843
3: rs116400033   1 51479  T  A 0.1829  0.0711 0.0370 1.262410 0.1829
4: rs146477069   1 54421  A  G 0.0352 -0.0240 0.0830 0.112102 0.0352
            ID          P
1:  rs58108140 0.42730011
2:    rs806731 0.74669974
3: rs116400033 0.05464998
4: rs146477069 0.77249913
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28531ecf45.tsv.gz
Reading header.
Importing VCF file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/MungeSumstats/extdata/ALSvcf.vcf
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	EBI-a-GCST005647	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'EBI-A-GCST005647' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
INFO column is actually AF, it will be converted.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	ES	SE	LP	AF	ID	P	
Summary statistics report:
   - 101 rows
   - 101 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Filtering SNPs based on INFO score.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28531ecf45.tsv.gz
Summary statistics report:
   - 99 rows (98% of original 101 rows)
   - 99 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2   INFO    BETA     SE       LP    FRQ
1:  rs58108140   1 10583  G  A 0.1589  0.0312 0.0393 0.369267 0.1589
2:    rs806731   1 30923  G  T 0.7843 -0.0114 0.0353 0.126854 0.7843
3: rs116400033   1 51479  T  A 0.1829  0.0711 0.0370 1.262410 0.1829
4: rs146477069   1 54421  A  G 0.0352 -0.0240 0.0830 0.112102 0.0352
            ID          P
1:  rs58108140 0.42730011
2:    rs806731 0.74669974
3: rs116400033 0.05464998
4: rs146477069 0.77249913
Returning data directly.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285993b9a6.tsv.gz
Reading header.
Importing VCF file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/MungeSumstats/extdata/ALSvcf.vcf
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	EBI-a-GCST005647	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'EBI-A-GCST005647' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
INFO column is actually AF, it will be converted.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	ES	SE	LP	AF	ID	P	
Summary statistics report:
   - 101 rows
   - 101 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Filtering SNPs based on INFO score.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285993b9a6.tsv.gz
Summary statistics report:
   - 99 rows (98% of original 101 rows)
   - 99 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2   INFO    BETA     SE       LP    FRQ
1:  rs58108140   1 10583  G  A 0.1589  0.0312 0.0393 0.369267 0.1589
2:    rs806731   1 30923  G  T 0.7843 -0.0114 0.0353 0.126854 0.7843
3: rs116400033   1 51479  T  A 0.1829  0.0711 0.0370 1.262410 0.1829
4: rs146477069   1 54421  A  G 0.0352 -0.0240 0.0830 0.112102 0.0352
            ID          P
1:  rs58108140 0.42730011
2:    rs806731 0.74669974
3: rs116400033 0.05464998
4: rs146477069 0.77249913
Returning data directly.
Converting summary statistics to Genomic Ranges.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2868adc4b4.tsv.gz
Reading header.
Importing VCF file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/MungeSumstats/extdata/ALSvcf.vcf
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	EBI-a-GCST005647	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'EBI-A-GCST005647' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
INFO column is actually AF, it will be converted.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	ES	SE	LP	AF	ID	P	
Summary statistics report:
   - 101 rows
   - 101 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Filtering SNPs based on INFO score.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2868adc4b4.tsv.gz
Summary statistics report:
   - 99 rows (98% of original 101 rows)
   - 99 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2   INFO    BETA     SE       LP    FRQ
1:  rs58108140   1 10583  G  A 0.1589  0.0312 0.0393 0.369267 0.1589
2:    rs806731   1 30923  G  T 0.7843 -0.0114 0.0353 0.126854 0.7843
3: rs116400033   1 51479  T  A 0.1829  0.0711 0.0370 1.262410 0.1829
4: rs146477069   1 54421  A  G 0.0352 -0.0240 0.0830 0.112102 0.0352
            ID          P
1:  rs58108140 0.42730011
2:    rs806731 0.74669974
3: rs116400033 0.05464998
4: rs146477069 0.77249913
Returning data directly.
Converting summary statistics to Genomic Ranges.
Converting summary statistics to VRanges.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e282663e0c3.tsv.gz
Reading header.
Importing VCF file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/MungeSumstats/extdata/ALSvcf.vcf
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	EBI-a-GCST005647	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'EBI-A-GCST005647' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
INFO column is actually AF, it will be converted.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	ES	SE	LP	AF	ID	P	
Summary statistics report:
   - 101 rows
   - 101 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Inferring genome build.
Loading reference genome data.
Loading reference genome data.
Inferred genome build: GRCH37
Checking SNP RSIDs.
Checking for merged allele column.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Filtering SNPs based on INFO score.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Warning: When method is an integer, must be >0.
2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e282663e0c3.tsv.gz
Summary statistics report:
   - 99 rows (98% of original 101 rows)
   - 99 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2   INFO    BETA     SE       LP    FRQ
1:  rs58108140   1 10583  G  A 0.1589  0.0312 0.0393 0.369267 0.1589
2:    rs806731   1 30923  G  T 0.7843 -0.0114 0.0353 0.126854 0.7843
3: rs116400033   1 51479  T  A 0.1829  0.0711 0.0370 1.262410 0.1829
4: rs146477069   1 54421  A  G 0.0352 -0.0240 0.0830 0.112102 0.0352
            ID          P
1:  rs58108140 0.42730011
2:    rs806731 0.74669974
3: rs116400033 0.05464998
4: rs146477069 0.77249913
Returning data directly.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285d018254.tsv.gz
Reading header.
Importing VCF file: /Library/Frameworks/R.framework/Versions/4.1/Resources/library/MungeSumstats/extdata/ALSvcf.vcf
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	EBI-a-GCST005647	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'EBI-A-GCST005647' data column.
0 empty column(s) detected.
VCF file has -log10 P-values, these will be converted to unadjusted p-values in the 'P' column.
Formatting INFO column.
INFO column is actually AF, it will be converted.
Standardising column headers.
First line of summary statistics file: 
CHR	BP	SNP	A1	A2	INFO	ES	SE	LP	AF	ID	P	
Ensuring parameters comply with LDSC format.

Setting `compute_z=TRUE` to comply with LDSC format.
Summary statistics report:
   - 101 rows
   - 101 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Checking for correct direction of A1 (reference) and A2 (alternative allele).
Loading reference genome data.
Reordering so first three column headers are SNP, CHR and BP in this order.
Reordering so the fourth and fifth columns are A1 and A2.
Checking for missing data.
Checking for duplicate columns.
Checking for duplicate SNPs from SNP ID.
Checking for SNPs with duplicated base-pair positions.
2 base-pair positions are duplicated in the sumstats file. These duplicates will be removed.
Filtering SNPs based on INFO score.
Filtering SNPs, ensuring SE>0.
Ensuring all SNPs have N<5 std dev above mean.
Removing 'chr' prefix from CHR.
Making X/Y CHR uppercase.
Computing Z-score from P using formula: `sign(BETA)*sqrt(stats::qchisq(P,1,lower=FALSE)`
Assigning N=1001 for all SNPs.
2 SNPs (2%) have FRQ values > 0.5. Conventionally the FRQ column is intended to show the minor/effect allele frequency.
The FRQ column was mapped from one of the following from the inputted  summary statistics file:
FRQ, EAF, MAF, FRQ_U, F_U, FREQUENCY, FREQ, FREQ_TESTED_ALLELE, FRQ_TESTED_ALLELE, FREQ_EFFECT_ALLELE, FRQ_EFFECT_ALLELE, EFFECT_ALLELE_FREQUENCY, EFFECT_ALLELE_FREQ, EFFECT_ALLELE_FRQ, A1FREQ, A1FRQ, A2FREQ, A2FRQ, ALLELE_FREQUENCY, ALLELE_FREQ, ALLELE_FRQ, AF, MINOR_AF, EFFECT_AF, A2_AF, EFF_AF, ALT_AF, ALTERNATIVE_AF, INC_AF, A_2_AF, TESTED_AF
As frq_is_maf=TRUE, the FRQ column will not be renamed. If the FRQ values were intended to represent major allele frequency,
set frq_is_maf=FALSE to rename the column as MAJOR_ALLELE_FRQ and differentiate it from minor/effect allele frequency.
Sorting coordinates.
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285d018254.tsv.gz
Summary statistics report:
   - 99 rows (98% of original 101 rows)
   - 99 unique variants
   - 0 genome-wide significant variants (P<5e-8)
   - 1 chromosomes
Successfully finished preparing sumstats file, preview:
Reading header.
           SNP CHR    BP A1 A2   INFO    BETA     SE       LP    FRQ
1:  rs58108140   1 10583  G  A 0.1589  0.0312 0.0393 0.369267 0.1589
2:    rs806731   1 30923  G  T 0.7843 -0.0114 0.0353 0.126854 0.7843
3: rs116400033   1 51479  T  A 0.1829  0.0711 0.0370 1.262410 0.1829
4: rs146477069   1 54421  A  G 0.0352 -0.0240 0.0830 0.112102 0.0352
            ID          P          Z    N
1:  rs58108140 0.42730011  0.7938202 1001
2:    rs806731 0.74669974 -0.3229941 1001
3: rs116400033 0.05464998  1.9216487 1001
4: rs146477069 0.77249913 -0.2891075 1001
Returning path to saved data.


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285794aad5.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28447ea92c
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	
Summary statistics report:
   - 93 rows
   - 93 unique variants
   - 20 chromosomes
Checking for multi-GWAS.
Checking for multiple RSIDs on one row.
Checking SNP RSIDs.
Checking for merged allele column.
Standardising column headers.
First line of summary statistics file: 
MarkerName	CHR	POS	A1	A2	EAF	Beta	SE	Pval	
Sorting coordinates.
.tsv


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28603c177d.tsv
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28603c177d.tsv
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28603c177d.tsv
.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e28350b0264.tsv.gz
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e28350b0264.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e28350b0264.tsv.gz
.tsv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

save_path suggests .gz output but tabix_index=TRUE Switching output to tabix-indexed format (.bgz).
Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285a9845d3.tsv.bgz
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285a9845d3.tsv.bgz
Converting full summary stats file to tabix format for fast querying...
Reading header.
Ensuring file is bgzipped.
Tabix-indexing file.
Reading header.
Tabular format detected.
Importing tabular bgz file: /tmp/RtmpVuXGOH/file12e285a9845d3.tsv.bgz
.tsv.bgz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2855fd7c30.tsv.bgz
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2855fd7c30.tsv.bgz
Converting full summary stats file to tabix format for fast querying...
Reading header.
Ensuring file is bgzipped.
Tabix-indexing file.
Reading header.
Tabular format detected.
Importing tabular bgz file: /tmp/RtmpVuXGOH/file12e2855fd7c30.tsv.bgz
.csv


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2852c91cc3.csv
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2852c91cc3.csv
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2852c91cc3.csv
.csv.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2845bdf386.csv.gz
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e2845bdf386.csv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e2845bdf386.csv.gz
.vcf


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

save_path suggests VCF output but write_vcf=FALSE. Switching output to tabular format (.tsv.gz).
Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e282a2fa611.tsv.gz
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e282a2fa611.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e282a2fa611.tsv.gz
.vcf.gz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

save_path suggests VCF output but write_vcf=FALSE. Switching output to tabular format (.tsv.gz).
Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285246e5f2.tsv.gz
Writing in tabular format ==> /tmp/RtmpVuXGOH/file12e285246e5f2.tsv.gz
Reading header.
Tabular format detected.
Importing tabular file: /tmp/RtmpVuXGOH/file12e285246e5f2.tsv.gz
.vcf


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2814e3a351.vcf.gz
Converting summary statistics to Genomic Ranges.
Converting summary statistics to VRanges.
Writing in VCF format ==> /tmp/RtmpVuXGOH/file12e2814e3a351.vcf.gz
Reading header.
Importing VCF file: /tmp/RtmpVuXGOH/file12e2814e3a351.vcf.gz
Reading VCF file.
Standardising column headers.
First line of summary statistics file: 
CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	GWAS	
Removing non-standard columns: QUAL, FILTER, FORMAT
Parsing 'GWAS' data column.
1 empty column(s) detected.
Formatting INFO column.
NOTE: All INFO scores are empty. Replacing all with 1.
.vcf


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e2826f9e1fc.vcf.gz
Converting summary statistics to Genomic Ranges.
Converting summary statistics to VRanges.
Writing in VCF format ==> /tmp/RtmpVuXGOH/file12e2826f9e1fc.vcf.gz
Compressing with bgzip and indexing with tabix.
Reading header.
Importing VCF file: /tmp/RtmpVuXGOH/file12e2826f9e1fc.vcf.bgz
Reading VCF file.
sumstats_file previously parsed with vcf2df.
Standardising column headers.
First line of summary statistics file: 
SNP	CHROM	BP	end	width	strand	paramRangeID	REF	ALT	QUAL	FILTER	AD_GWAS.1	AD_GWAS.2	DP	FT	SNP	FRQ	BETA	SE	P	PARSED	
Removing non-standard columns: END, WIDTH, STRAND, PARAMRANGEID, QUAL, FILTER, AD_GWAS.1, AD_GWAS.2, DP, FT, PARSED
Parsing 'GWAS' data column.
0 empty column(s) detected.
.vcf.bgz


******::NOTE::******
- Formatted results will be saved to `tempdir()` by default.
- This means all formatted summary stats will be deletedupon ending the R session.
- To keep formatted summary stats, change `save_path` ( e.g. `save_path=file.path('./formatted',basename(path))` ),  or make sure to copy files elsewhere after processing ( e.g. `file.copy(save_path, './formatted/' )`.
********************

Formatted summary statistics will be saved to ==> /tmp/RtmpVuXGOH/file12e285f637b61.vcf.gz
Converting summary statistics to Genomic Ranges.
Converting summary statistics to VRanges.
Writing in VCF format ==> /tmp/RtmpVuXGOH/file12e285f637b61.vcf.gz
Compressing with bgzip and indexing with tabix.
Reading header.
Importing VCF file: /tmp/RtmpVuXGOH/file12e285f637b61.vcf.bgz
Reading VCF file.
sumstats_file previously parsed with vcf2df.
Standardising column headers.
First line of summary statistics file: 
SNP	CHROM	BP	end	width	strand	paramRangeID	REF	ALT	QUAL	FILTER	AD_GWAS.1	AD_GWAS.2	DP	FT	SNP	FRQ	BETA	SE	P	PARSED	
Removing non-standard columns: END, WIDTH, STRAND, PARAMRANGEID, QUAL, FILTER, AD_GWAS.1, AD_GWAS.2, DP, FT, PARSED
Parsing 'GWAS' data column.
0 empty column(s) detected.
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 122 ]
> 
> proc.time()
   user  system elapsed 
756.454  44.068 808.362