Package: SNPRelate

Version: 1.12.2

Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --no-vignettes --timings SNPRelate_1.12.2.tar.gz

StartedAt: 2018-04-12 09:48:07 -0400 (Thu, 12 Apr 2018)

EndedAt: 2018-04-12 09:50:25 -0400 (Thu, 12 Apr 2018)

EllapsedTime: 138.1 seconds

RetCode: 0

Status:  OK

CheckDir: SNPRelate.Rcheck

Warnings: 0

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###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --no-vignettes --timings SNPRelate_1.12.2.tar.gz
###
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* using log directory ‘/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck’
* using R version 3.4.4 (2018-03-15)
* using platform: x86_64-apple-darwin15.6.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘SNPRelate/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘SNPRelate’ version ‘1.12.2’
* 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 ‘SNPRelate’ can be installed ... OK
* checking installed package size ... NOTE
  installed size is  5.4Mb
  sub-directories of 1Mb or more:
    doc   3.3Mb
* 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 line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking compiled code ... OK
* checking installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.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: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/00check.log’
for details.

* installing *source* package ‘SNPRelate’ ...
** libs
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c ConvToGDS.cpp -o ConvToGDS.o
clang -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c R_SNPRelate.c -o R_SNPRelate.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c SNPRelate.cpp -o SNPRelate.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c ThreadPool.cpp -o ThreadPool.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c dGenGWAS.cpp -o dGenGWAS.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c dVect.cpp -o dVect.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genBeta.cpp -o genBeta.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genEIGMIX.cpp -o genEIGMIX.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genFst.cpp -o genFst.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genHWE.cpp -o genHWE.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genIBD.cpp -o genIBD.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genIBS.cpp -o genIBS.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genKING.cpp -o genKING.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genLD.cpp -o genLD.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genPCA.cpp -o genPCA.o
clang++  -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG -DUSING_R -I. -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/gdsfmt/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c genSlideWin.cpp -o genSlideWin.o
clang++ -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o SNPRelate.so ConvToGDS.o R_SNPRelate.o SNPRelate.o ThreadPool.o dGenGWAS.o dVect.o genBeta.o genEIGMIX.o genFst.o genHWE.o genIBD.o genIBS.o genKING.o genLD.o genPCA.o genSlideWin.o -L/usr/local/gfortran/lib/gcc/x86_64-apple-darwin15/6.1.0 -L/usr/local/gfortran/lib -lgfortran -lquadmath -lm -L/Library/Frameworks/R.framework/Resources/lib -lRblas -L/Library/Frameworks/R.framework/Resources/lib -lRlapack -lpthread -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/libs
** R
** data
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (SNPRelate)

R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (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.

> BiocGenerics:::testPackage("SNPRelate")
SNPRelate -- supported by Streaming SIMD Extensions 2 (SSE2)
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 1000 SNPs
    using 1 (CPU) core.
    method: covariance
LD matrix:    the sum of all selected genotypes (0,1,2) = 283058
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 1000 SNPs
    using 1 (CPU) core.
    method: correlation
LD matrix:    the sum of all selected genotypes (0,1,2) = 283058
FUNCTION: SNPGDSFileClass
FUNCTION: SNPRelate-package
Start snpgdsBED2GDS ...
	BED file: "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/plinkhapmap.bed.gz" in the SNP-major mode (Sample X SNP)
	FAM file: "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/plinkhapmap.fam.gz", DONE.
	BIM file: "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/plinkhapmap.bim.gz", DONE.
Thu Apr 12 09:49:49 2018 	store sample id, snp id, position, and chromosome.
	start writing: 60 samples, 5000 SNPs ...
 	Thu Apr 12 09:49:49 2018	0%
 	Thu Apr 12 09:49:49 2018	100%
Thu Apr 12 09:49:49 2018 	Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'HapMap.gds' (104.6K)
    # of fragments: 38
    save to 'HapMap.gds.tmp'
    rename 'HapMap.gds.tmp' (104.4K, reduced: 240B)
    # of fragments: 18
Principal Component Analysis (PCA) on genotypes:
Excluding 203 SNPs on non-autosomes
Excluding 28 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 60 samples, 4,769 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 124273
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:49:49 2018    (internal increment: 21228)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:49:49 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:49:49 2018    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 2446510
Thu Apr 12 09:49:49 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 1s
Thu Apr 12 09:49:50 2018    Done.
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Thu Apr 12 09:49:50 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:49:50 2018    Done.
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 200 SNPs
    using 1 (CPU) core.
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 55417
FUNCTION: hapmap_geno
FUNCTION: snpgdsAdmixPlot
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:49:51 2018    (internal increment: 4564)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:49:51 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:49:51 2018    Done.
FUNCTION: snpgdsAdmixProp
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:49:51 2018    (internal increment: 4564)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:49:51 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:49:51 2018    Done.
FUNCTION: snpgdsAlleleSwitch
Strand-switching at 50 SNP locus/loci.
Unable to determine switching at 10 SNP locus/loci.
FUNCTION: snpgdsApartSelection
Thu Apr 12 09:49:52 2018	Chromosome 1, # of SNPs: 365
Thu Apr 12 09:49:52 2018	Chromosome 2, # of SNPs: 370
Thu Apr 12 09:49:52 2018	Chromosome 3, # of SNPs: 314
Thu Apr 12 09:49:52 2018	Chromosome 4, # of SNPs: 294
Thu Apr 12 09:49:52 2018	Chromosome 5, # of SNPs: 291
Thu Apr 12 09:49:52 2018	Chromosome 6, # of SNPs: 280
Thu Apr 12 09:49:52 2018	Chromosome 7, # of SNPs: 245
Thu Apr 12 09:49:52 2018	Chromosome 8, # of SNPs: 232
Thu Apr 12 09:49:52 2018	Chromosome 9, # of SNPs: 203
Thu Apr 12 09:49:52 2018	Chromosome 10, # of SNPs: 224
Thu Apr 12 09:49:52 2018	Chromosome 11, # of SNPs: 227
Thu Apr 12 09:49:52 2018	Chromosome 12, # of SNPs: 215
Thu Apr 12 09:49:52 2018	Chromosome 13, # of SNPs: 175
Thu Apr 12 09:49:52 2018	Chromosome 14, # of SNPs: 147
Thu Apr 12 09:49:52 2018	Chromosome 15, # of SNPs: 127
Thu Apr 12 09:49:52 2018	Chromosome 16, # of SNPs: 128
Thu Apr 12 09:49:52 2018	Chromosome 17, # of SNPs: 112
Thu Apr 12 09:49:52 2018	Chromosome 18, # of SNPs: 127
Thu Apr 12 09:49:52 2018	Chromosome 19, # of SNPs: 76
Thu Apr 12 09:49:52 2018	Chromosome 20, # of SNPs: 107
Thu Apr 12 09:49:52 2018	Chromosome 21, # of SNPs: 63
Thu Apr 12 09:49:52 2018	Chromosome 22, # of SNPs: 54
Thu Apr 12 09:49:52 2018	Chromosome 23, # of SNPs: 215
Total # of SNPs selected:4591
FUNCTION: snpgdsBED2GDS
Start snpgdsBED2GDS ...
	BED file: "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/plinkhapmap.bed.gz" in the SNP-major mode (Sample X SNP)
	FAM file: "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/plinkhapmap.fam.gz", DONE.
	BIM file: "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/plinkhapmap.bim.gz", DONE.
Thu Apr 12 09:49:52 2018 	store sample id, snp id, position, and chromosome.
	start writing: 60 samples, 5000 SNPs ...
 	Thu Apr 12 09:49:52 2018	0%
 	Thu Apr 12 09:49:52 2018	100%
Thu Apr 12 09:49:52 2018 	Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'HapMap.gds' (104.6K)
    # of fragments: 38
    save to 'HapMap.gds.tmp'
    rename 'HapMap.gds.tmp' (104.4K, reduced: 240B)
    # of fragments: 18
FUNCTION: snpgdsClose
FUNCTION: snpgdsCombineGeno
Create test.gds with 558 samples and 9087 SNPs
	Open the gds file /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/hapmap_geno.gds.
		0 strands of SNP loci need to be switched.
	Open the gds file /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/hapmap_geno.gds.
		0 strands of SNP loci need to be switched.
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test.gds 
The total number of samples: 558 
The total number of SNPs: 9087 
SNP genotypes are stored in individual-major mode (SNP X Sample).
FUNCTION: snpgdsCreateGeno
Principal Component Analysis (PCA) on genotypes:
Excluding 42 SNPs on non-autosomes
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 958 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 264760
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:49:53 2018    (internal increment: 4564)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:49:53 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:49:53 2018    Done.
FUNCTION: snpgdsCreateGenoSet
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 75.42%, 540/716
Chromosome 2: 72.24%, 536/742
Chromosome 3: 74.71%, 455/609
Chromosome 4: 73.31%, 412/562
Chromosome 5: 77.03%, 436/566
Chromosome 6: 75.58%, 427/565
Chromosome 7: 75.42%, 356/472
Chromosome 8: 71.31%, 348/488
Chromosome 9: 77.88%, 324/416
Chromosome 10: 74.33%, 359/483
Chromosome 11: 77.40%, 346/447
Chromosome 12: 76.81%, 328/427
Chromosome 13: 75.58%, 260/344
Chromosome 14: 76.95%, 217/282
Chromosome 15: 76.34%, 200/262
Chromosome 16: 72.66%, 202/278
Chromosome 17: 74.40%, 154/207
Chromosome 18: 73.68%, 196/266
Chromosome 19: 85.00%, 102/120
Chromosome 20: 71.62%, 164/229
Chromosome 21: 76.98%, 97/126
Chromosome 22: 75.86%, 88/116
6,547 markers are selected in total.
Create a GDS genotype file:
The new dataset consists of 279 samples and 6547 SNPs
    write sample.id
    write snp.id
    write snp.rs.id
    write snp.position
    write snp.chromosome
    write snp.allele
SNP genotypes are stored in SNP-major mode (Sample X SNP).
FUNCTION: snpgdsCutTree
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Thu Apr 12 09:49:53 2018	0%
Dissimilarity:	Thu Apr 12 09:49:54 2018	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
Create 4 groups.
FUNCTION: snpgdsDiss
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Thu Apr 12 09:49:55 2018	0%
Dissimilarity:	Thu Apr 12 09:49:56 2018	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsDrawTree
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Thu Apr 12 09:49:57 2018	0%
Dissimilarity:	Thu Apr 12 09:49:58 2018	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsEIGMIX
Eigen-analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Eigen-analysis:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:49:59 2018    (internal increment: 4564)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:49:59 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:49:59 2018    Done.
FUNCTION: snpgdsErrMsg
FUNCTION: snpgdsExampleFileName
FUNCTION: snpgdsFst
Fst estimation on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
Method: Weir & Cockerham, 1984
# of Populations: 4
    CEU (92), HCB (47), JPT (47), YRI (93)
Fst estimation on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
Method: Weir & Hill, 2002
# of Populations: 4
    CEU (92), HCB (47), JPT (47), YRI (93)
FUNCTION: snpgdsGDS2BED
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: 0.95)
Converting from GDS to PLINK binary PED:
Working space: 279 samples, 8722 SNPs
Output a BIM file.
Output a BED file ...
		Thu Apr 12 09:49:59 2018	0%
		Thu Apr 12 09:49:59 2018	100%
Done.
FUNCTION: snpgdsGDS2Eigen
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: 0.95)
Converting from GDS to EIGENSOFT:
	save to *.snp: 8722 snps
	save to *.ind: 279 samples
	Output: 	Thu Apr 12 09:49:59 2018	0%
	Output: 	Thu Apr 12 09:50:00 2018	100%
Done.
FUNCTION: snpgdsGDS2PED
Converting from GDS to PLINK PED:
	Output a MAP file DONE.
	Output a PED file ...
		Output: 	Thu Apr 12 09:50:00 2018	0%
		Output: 	Thu Apr 12 09:50:00 2018	100%
FUNCTION: snpgdsGEN2GDS
running snpgdsGEN2GDS ...
FUNCTION: snpgdsGRM
Genetic Relationship Matrix (GRM, GCTA):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:00 2018    (internal increment: 4564)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 1s
Thu Apr 12 09:50:01 2018    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:01 2018    (internal increment: 4564)

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Saving to the GDS file:

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Thu Apr 12 09:50:01 2018    Done.
FUNCTION: snpgdsGetGeno
Genotype matrix: 1000 SNPs X 279 samples
Genotype matrix: 279 samples X 1000 SNPs
FUNCTION: snpgdsHCluster
Individual dissimilarity analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Dissimilarity:    the sum of all selected genotypes (0,1,2) = 2446510
Dissimilarity:	Thu Apr 12 09:50:01 2018	0%
Dissimilarity:	Thu Apr 12 09:50:02 2018	100%
Determine groups by permutation (Z threshold: 15, outlier threshold: 5):
Create 3 groups.
FUNCTION: snpgdsHWE
Keeping 716 SNPs according to chromosome 1
Excluding 160 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
FUNCTION: snpgdsIBDKING
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:03 2018    (internal increment: 65536)

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Thu Apr 12 09:50:03 2018    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
# of families: 20, and within- and between-family relationship are estimated differently.
Relationship inference in the presence of population stratification.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:04 2018    (internal increment: 65536)

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[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:04 2018    Done.
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
Relationship inference in a homogeneous population.
KING IBD:    the sum of all selected genotypes (0,1,2) = 702139
Thu Apr 12 09:50:04 2018    (internal increment: 65536)

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Thu Apr 12 09:50:04 2018    Done.
FUNCTION: snpgdsIBDMLE
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,581 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
Working space: 30 samples, 7,142 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 54.75%, 392/716
Chromosome 2: 54.45%, 404/742
Chromosome 3: 55.67%, 339/609
Chromosome 4: 56.94%, 320/562
Chromosome 5: 56.71%, 321/566
Chromosome 6: 52.74%, 298/565
Chromosome 7: 55.72%, 263/472
Chromosome 8: 50.41%, 246/488
Chromosome 9: 54.33%, 226/416
Chromosome 10: 50.10%, 242/483
Chromosome 11: 54.81%, 245/447
Chromosome 12: 55.04%, 235/427
Chromosome 13: 53.49%, 184/344
Chromosome 14: 55.67%, 157/282
Chromosome 15: 54.58%, 143/262
Chromosome 16: 54.68%, 152/278
Chromosome 17: 55.56%, 115/207
Chromosome 18: 55.64%, 148/266
Chromosome 19: 66.67%, 80/120
Chromosome 20: 52.84%, 121/229
Chromosome 21: 50.79%, 64/126
Chromosome 22: 50.86%, 59/116
4,754 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 30 samples, 250 SNPs
    using 1 (CPU) core
MLE IBD:    the sum of all selected genotypes (0,1,2) = 7195
MLE IBD:	Thu Apr 12 09:50:04 2018	0%
MLE IBD:	Thu Apr 12 09:50:05 2018	100%
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.480, sd: 0.281
MLE IBD:    the sum of all selected genotypes (0,1,2) = 5991
MLE IBD:	Thu Apr 12 09:50:05 2018	0%
MLE IBD:	Thu Apr 12 09:50:05 2018	100%
FUNCTION: snpgdsIBDMLELogLik
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,581 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
Working space: 30 samples, 7,142 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 54.75%, 392/716
Chromosome 2: 54.45%, 404/742
Chromosome 3: 55.67%, 339/609
Chromosome 4: 56.94%, 320/562
Chromosome 5: 56.71%, 321/566
Chromosome 6: 52.74%, 298/565
Chromosome 7: 55.72%, 263/472
Chromosome 8: 50.41%, 246/488
Chromosome 9: 54.33%, 226/416
Chromosome 10: 50.10%, 242/483
Chromosome 11: 54.81%, 245/447
Chromosome 12: 55.04%, 235/427
Chromosome 13: 53.49%, 184/344
Chromosome 14: 55.67%, 157/282
Chromosome 15: 54.58%, 143/262
Chromosome 16: 54.68%, 152/278
Chromosome 17: 55.56%, 115/207
Chromosome 18: 55.64%, 148/266
Chromosome 19: 66.67%, 80/120
Chromosome 20: 52.84%, 121/229
Chromosome 21: 50.79%, 64/126
Chromosome 22: 50.86%, 59/116
4,754 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 30 samples, 250 SNPs
    using 1 (CPU) core
MLE IBD:    the sum of all selected genotypes (0,1,2) = 7195
MLE IBD:	Thu Apr 12 09:50:05 2018	0%
MLE IBD:	Thu Apr 12 09:50:05 2018	100%
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.480, sd: 0.281
MLE IBD:    the sum of all selected genotypes (0,1,2) = 5991
MLE IBD:	Thu Apr 12 09:50:05 2018	0%
MLE IBD:	Thu Apr 12 09:50:05 2018	100%
FUNCTION: snpgdsIBDMoM
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 92 samples, 7,506 SNPs
    using 1 (CPU) core
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 702139
Thu Apr 12 09:50:06 2018    (internal increment: 65536)

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Thu Apr 12 09:50:06 2018    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 93 samples, 8,160 SNPs
    using 1 (CPU) core
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Thu Apr 12 09:50:06 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:06 2018    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 93 samples, 8,160 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.500, sd: 0.315
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Thu Apr 12 09:50:06 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:06 2018    Done.
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 8,160 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.500, sd: 0.315
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 203285
Thu Apr 12 09:50:06 2018    (internal increment: 65536)

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Thu Apr 12 09:50:06 2018    Done.
FUNCTION: snpgdsIBDSelection
IBD analysis (PLINK method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 563 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 93 samples, 8,160 SNPs
    using 1 (CPU) core
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 755648
Thu Apr 12 09:50:06 2018    (internal increment: 65536)

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Thu Apr 12 09:50:06 2018    Done.
FUNCTION: snpgdsIBS
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Thu Apr 12 09:50:06 2018    (internal increment: 65536)

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[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:06 2018    Done.
FUNCTION: snpgdsIBSNum
Identity-By-State (IBS) analysis on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
IBS:    the sum of all selected genotypes (0,1,2) = 2446510
Thu Apr 12 09:50:06 2018    (internal increment: 65536)

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[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:06 2018    Done.
FUNCTION: snpgdsIndInb
Estimate individual inbreeding coefficients:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
FUNCTION: snpgdsIndInbCoef
FUNCTION: snpgdsIndivBeta
Individual Inbreeding and Relatedness (beta estimator):
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
Individual Beta:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:07 2018    (internal increment: 65536)

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[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:07 2018    Done.
FUNCTION: snpgdsLDMat
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 262 SNPs
    using 1 (CPU) core.
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 73989
Linkage Disequilibrium (LD) estimation on genotypes:
Working space: 279 samples, 262 SNPs
    using 1 (CPU) core.
    sliding window size: 250 
    method: composite
LD matrix:    the sum of all selected genotypes (0,1,2) = 73989
FUNCTION: snpgdsLDpair
FUNCTION: snpgdsLDpruning
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 75.42%, 540/716
Chromosome 2: 72.24%, 536/742
Chromosome 3: 74.71%, 455/609
Chromosome 4: 73.31%, 412/562
Chromosome 5: 77.03%, 436/566
Chromosome 6: 75.58%, 427/565
Chromosome 7: 75.42%, 356/472
Chromosome 8: 71.31%, 348/488
Chromosome 9: 77.88%, 324/416
Chromosome 10: 74.33%, 359/483
Chromosome 11: 77.40%, 346/447
Chromosome 12: 76.81%, 328/427
Chromosome 13: 75.58%, 260/344
Chromosome 14: 76.95%, 217/282
Chromosome 15: 76.34%, 200/262
Chromosome 16: 72.66%, 202/278
Chromosome 17: 74.40%, 154/207
Chromosome 18: 73.68%, 196/266
Chromosome 19: 85.00%, 102/120
Chromosome 20: 71.62%, 164/229
Chromosome 21: 76.98%, 97/126
Chromosome 22: 75.86%, 88/116
6,547 markers are selected in total.
FUNCTION: snpgdsMergeGRM
Genetic Relationship Matrix (GRM, GCTA):
Excluding 2,288 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 6,800 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 1908966
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:07 2018    (internal increment: 4564)

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[==================================================] 100%, completed in 1s
Thu Apr 12 09:50:08 2018    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 5,688 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 3,400 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 951558
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:08 2018    (internal increment: 4564)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Saving to the GDS file:

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:08 2018    Done.
Genetic Relationship Matrix (GRM, GCTA):
Excluding 5,688 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 3,400 SNPs
    using 1 (CPU) core
GRM Calculation:    the sum of all selected genotypes (0,1,2) = 957408
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:08 2018    (internal increment: 4564)

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Saving to the GDS file:

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Thu Apr 12 09:50:08 2018    Done.
GRM merging:
    open 'tmp1.gds' (3,400 variants)
    open 'tmp2.gds' (3,400 variants)
Weight: 0.5, 0.5
Output: tmp.gds

[..................................................]  0%, ETC: ---    
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GRM merging:
    open 'tmp1.gds' (3,400 variants)
    open 'tmp2.gds' (3,400 variants)
Weight: 0.5, 0.5

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FUNCTION: snpgdsOpen
FUNCTION: snpgdsOption
FUNCTION: snpgdsPCA
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:09 2018    (internal increment: 4564)

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Thu Apr 12 09:50:09 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:50:09 2018    Done.
FUNCTION: snpgdsPCACorr
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:10 2018    (internal increment: 4564)

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[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:10 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:50:10 2018    Done.
SNP Correlation:
Working space: 279 samples, 9088 SNPs
    using 1 (CPU) core
    using the top 4 eigenvectors
Correlation:    the sum of all selected genotypes (0,1,2) = 2553065
Thu Apr 12 09:50:10 2018    (internal increment: 36524)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:10 2018    Done.
SNP Correlation:
Working space: 279 samples, 9088 SNPs
    using 1 (CPU) core
    using the top 4 eigenvectors
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 2553065
Thu Apr 12 09:50:10 2018

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[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:10 2018    Done.
FUNCTION: snpgdsPCASNPLoading
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:10 2018    (internal increment: 4564)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:10 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:50:10 2018    Done.
SNP loading:
Working space: 279 samples, 8722 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 2446510
Thu Apr 12 09:50:10 2018    (internal increment: 36524)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:10 2018    Done.
FUNCTION: snpgdsPCASampLoading
Principal Component Analysis (PCA) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 8,722 SNPs
    using 1 (CPU) core
PCA:    the sum of all selected genotypes (0,1,2) = 2446510
CPU capabilities: Double-Precision SSE2
Thu Apr 12 09:50:10 2018    (internal increment: 4564)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 1s
Thu Apr 12 09:50:11 2018    Begin (eigenvalues and eigenvectors)
Thu Apr 12 09:50:11 2018    Done.
SNP loading:
Working space: 279 samples, 8722 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 2446510
Thu Apr 12 09:50:11 2018    (internal increment: 36524)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:11 2018    Done.
Sample loading:
Working space: 100 samples, 8722 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 878146
Thu Apr 12 09:50:11 2018    (internal increment: 65536)

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[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:11 2018    Done.
FUNCTION: snpgdsPED2GDS
Converting from GDS to PLINK PED:
	Output a MAP file DONE.
	Output a PED file ...
		Output: 	Thu Apr 12 09:50:11 2018	0%
		Output: 	Thu Apr 12 09:50:11 2018	100%
PLINK PED/MAP to GDS Format:
Import 9088 variants from 'tmp.map'
Chromosome:
  1  10  11  12  13  14  15  16  17  18  19   2  20  21  22   3   4   5   6   7 
716 483 447 427 344 282 262 278 207 266 120 742 229 126 116 609 562 566 565 472 
  8   9   X 
488 416 365 
Reading 'tmp.ped'
Output: 'test.gds'
Import 279 samples
Transpose the genotypic matrix ...
Done.
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (1.3M)
    # of fragments: 50
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (711.4K, reduced: 618.7K)
    # of fragments: 26
FUNCTION: snpgdsPairIBD
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,646 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
Working space: 93 samples, 7,077 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 62.29%, 446/716
Chromosome 2: 62.40%, 463/742
Chromosome 3: 60.76%, 370/609
Chromosome 4: 64.59%, 363/562
Chromosome 5: 62.54%, 354/566
Chromosome 6: 60.00%, 339/565
Chromosome 7: 62.71%, 296/472
Chromosome 8: 58.61%, 286/488
Chromosome 9: 62.98%, 262/416
Chromosome 10: 60.66%, 293/483
Chromosome 11: 62.86%, 281/447
Chromosome 12: 63.00%, 269/427
Chromosome 13: 63.08%, 217/344
Chromosome 14: 63.48%, 179/282
Chromosome 15: 63.36%, 166/262
Chromosome 16: 61.87%, 172/278
Chromosome 17: 65.70%, 136/207
Chromosome 18: 59.02%, 157/266
Chromosome 19: 68.33%, 82/120
Chromosome 20: 67.25%, 154/229
Chromosome 21: 61.11%, 77/126
Chromosome 22: 57.76%, 67/116
5,429 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.506, sd: 0.300
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6339
MLE IBD:	Thu Apr 12 09:50:14 2018	0%
MLE IBD:	Thu Apr 12 09:50:14 2018	100%
IBD analysis (PLINK method of moment) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.506, sd: 0.300
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 6339
Thu Apr 12 09:50:14 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:14 2018    Done.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.506, sd: 0.300
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6339
MLE IBD:	Thu Apr 12 09:50:14 2018	0%
MLE IBD:	Thu Apr 12 09:50:14 2018	100%
Genotype matrix: 250 SNPs X 25 samples
[1] -364.4667
[1] -377.9771
[1] -390.3299
[1] -380.5342
[1] -378.2092
[1] -383.641
[1] -364.5406
[1] -375.196
[1] -383.5752
[1] -385.7771
[1] -368.6237
[1] -390.7766
[1] -367.5082
[1] -383.595
[1] -385.7602
[1] -378.5134
[1] -388.3292
[1] -376.4419
[1] -378.3509
[1] -386.8318
[1] -385.3803
[1] -382.988
[1] -369.9328
[1] -383.3912
FUNCTION: snpgdsPairIBDMLELogLik
SNP pruning based on LD:
Excluding 365 SNPs on non-autosomes
Excluding 1,646 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.05)
Working space: 93 samples, 7,077 SNPs
    using 1 (CPU) core
    sliding window: 500,000 basepairs, Inf SNPs
    |LD| threshold: 0.2
    method: composite
Chromosome 1: 62.29%, 446/716
Chromosome 2: 62.40%, 463/742
Chromosome 3: 60.76%, 370/609
Chromosome 4: 64.59%, 363/562
Chromosome 5: 62.54%, 354/566
Chromosome 6: 60.00%, 339/565
Chromosome 7: 62.71%, 296/472
Chromosome 8: 58.61%, 286/488
Chromosome 9: 62.98%, 262/416
Chromosome 10: 60.66%, 293/483
Chromosome 11: 62.86%, 281/447
Chromosome 12: 63.00%, 269/427
Chromosome 13: 63.08%, 217/344
Chromosome 14: 63.48%, 179/282
Chromosome 15: 63.36%, 166/262
Chromosome 16: 61.87%, 172/278
Chromosome 17: 65.70%, 136/207
Chromosome 18: 59.02%, 157/266
Chromosome 19: 68.33%, 82/120
Chromosome 20: 67.25%, 154/229
Chromosome 21: 61.11%, 77/126
Chromosome 22: 57.76%, 67/116
5,429 markers are selected in total.
Identity-By-Descent analysis (MLE) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.506, sd: 0.300
MLE IBD:    the sum of all selected genotypes (0,1,2) = 6339
MLE IBD:	Thu Apr 12 09:50:15 2018	0%
MLE IBD:	Thu Apr 12 09:50:15 2018	100%
IBD analysis (PLINK method of moment) on genotypes:
Excluding 8,838 SNPs (non-autosomes or non-selection)
Excluding 0 SNP (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 25 samples, 250 SNPs
    using 1 (CPU) core
Specifying allele frequencies, mean: 0.506, sd: 0.300
*** A correction factor based on allele count is not used, since the allele frequencies are specified.
PLINK IBD:    the sum of all selected genotypes (0,1,2) = 6339
Thu Apr 12 09:50:15 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:15 2018    Done.
Genotype matrix: 250 SNPs X 25 samples
[1] -364.4667
[1] -377.9771
[1] -390.3299
[1] -380.5342
[1] -378.2092
[1] -383.641
[1] -364.5406
[1] -375.196
[1] -383.5752
[1] -385.7771
[1] -368.6237
[1] -390.7766
[1] -367.5082
[1] -383.595
[1] -385.7602
[1] -378.5134
[1] -388.3292
[1] -376.4419
[1] -378.3509
[1] -386.8318
[1] -385.3803
[1] -382.988
[1] -369.9328
[1] -383.3912
FUNCTION: snpgdsPairScore
Excluding 365 SNPs on non-autosomes
Working space: 120 samples, 8723 SNPs
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
Working space: 120 samples, 8723 SNPs
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
Working space: 120 samples, 8723 SNPs
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
Working space: 120 samples, 8723 SNPs
Method: IBS
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
Working space: 120 samples, 8723 SNPs
Method: IBS
Output: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/tmp.gds
Genotype Score:    the sum of all selected genotypes (0,1,2) = 1050236
FUNCTION: snpgdsSNPList
FUNCTION: snpgdsSNPListClass
FUNCTION: snpgdsSNPListIntersect
FUNCTION: snpgdsSNPListStrand
FUNCTION: snpgdsSNPRateFreq
FUNCTION: snpgdsSampMissRate
FUNCTION: snpgdsSelectSNP
Excluding 365 SNPs on non-autosomes
Excluding 1,221 SNPs (monomorphic: TRUE, MAF: 0.05, missing rate: 0.95)
FUNCTION: snpgdsSlidingWindow
Sliding Window Analysis:
Excluding 8 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
Working space: 279 samples, 9,080 SNPs
    using 1 (CPU) core
    window size: 500000, shift: 100000 (basepair)
Chromosome Set: 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23
Thu Apr 12 09:50:15 2018, Chromosome 1 (716 SNPs), 2448 windows
Thu Apr 12 09:50:16 2018, Chromosome 2 (742 SNPs), 2416 windows
Thu Apr 12 09:50:16 2018, Chromosome 3 (609 SNPs), 1985 windows
Thu Apr 12 09:50:16 2018, Chromosome 4 (562 SNPs), 1894 windows
Thu Apr 12 09:50:16 2018, Chromosome 5 (566 SNPs), 1797 windows
Thu Apr 12 09:50:16 2018, Chromosome 6 (565 SNPs), 1694 windows
Thu Apr 12 09:50:16 2018, Chromosome 7 (472 SNPs), 1573 windows
Thu Apr 12 09:50:16 2018, Chromosome 8 (488 SNPs), 1445 windows
Thu Apr 12 09:50:16 2018, Chromosome 9 (416 SNPs), 1393 windows
Thu Apr 12 09:50:16 2018, Chromosome 10 (483 SNPs), 1343 windows
Thu Apr 12 09:50:16 2018, Chromosome 11 (447 SNPs), 1338 windows
Thu Apr 12 09:50:16 2018, Chromosome 12 (427 SNPs), 1316 windows
Thu Apr 12 09:50:16 2018, Chromosome 13 (344 SNPs), 948 windows
Thu Apr 12 09:50:16 2018, Chromosome 14 (281 SNPs), 847 windows
Thu Apr 12 09:50:16 2018, Chromosome 15 (262 SNPs), 774 windows
Thu Apr 12 09:50:16 2018, Chromosome 16 (278 SNPs), 873 windows
Thu Apr 12 09:50:16 2018, Chromosome 17 (207 SNPs), 773 windows
Thu Apr 12 09:50:16 2018, Chromosome 18 (266 SNPs), 753 windows
Thu Apr 12 09:50:16 2018, Chromosome 19 (120 SNPs), 627 windows
Thu Apr 12 09:50:16 2018, Chromosome 20 (229 SNPs), 602 windows
Thu Apr 12 09:50:16 2018, Chromosome 21 (126 SNPs), 311 windows
Thu Apr 12 09:50:16 2018, Chromosome 22 (116 SNPs), 312 windows
Thu Apr 12 09:50:16 2018, Chromosome 23 (358 SNPs), 1507 windows
Thu Apr 12 09:50:16 2018 	Done.
FUNCTION: snpgdsSummary
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/hapmap_geno.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
FUNCTION: snpgdsTranspose
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
SNP genotypes: 279 samples, 9088 SNPs
Genotype matrix is being transposed ...
Clean up the fragments of GDS file:
    open the file 'test.gds' (1.3M)
    # of fragments: 28
    save to 'test.gds.tmp'
    rename 'test.gds.tmp' (709.6K, reduced: 619.1K)
    # of fragments: 26
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test.gds 
The total number of samples: 279 
The total number of SNPs: 9088 
SNP genotypes are stored in individual-major mode (SNP X Sample).
FUNCTION: snpgdsVCF2GDS
##fileformat=VCFv4.1
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	NA00001	NA00002	NA00003
20	14370	rs6054257	G	A	29	PASS	NS=3;DP=14;AF=0.5;DB;H2	GT:GQ:DP:HQ	0|0:48:1:51,51	1|0:48:8:51,51	1/1:43:5:.,.
20	17330	.	T	A	3	q10	NS=3;DP=11;AF=0.017	GT:GQ:DP:HQ	0|0:49:3:58,50	0|1:3:5:65,3	0/0:41:3
20	1110696	rs6040355	A	G,T	67	PASS	NS=2;DP=10;AF=0.333,0.667;AA=T;DB	GT:GQ:DP:HQ	1|2:21:6:23,27	2|1:2:0:18,2	2/2:35:4
20	1230237	.	T	.	47	PASS	NS=3;DP=13;AA=T	GT:GQ:DP:HQ	0|0:54:7:56,60	0|0:48:4:51,51	0/0:61:2
20	1234567	microsat1	GTC	G,GTCT	50	PASS	NS=3;DP=9;AA=G	GT:GQ:DP	0/1:35:4	0/2:17:2	1/1:40:3
VCF Format ==> SNP GDS Format
Method: exacting biallelic SNPs
Number of samples: 3
Parsing "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf" ...
	import 2 variants.
+ genotype   { Bit2 3x2, 2B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test1.gds' (2.4K)
    # of fragments: 39
    save to 'test1.gds.tmp'
    rename 'test1.gds.tmp' (2.2K, reduced: 228B)
    # of fragments: 20
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test1.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
VCF Format ==> SNP GDS Format
Method: exacting biallelic SNPs
Number of samples: 3
Parsing "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf" ...
	import 2 variants.
+ genotype   { Bit2 3x2, 2B } *
SNP genotypes: 3 samples, 2 SNPs
Genotype matrix is being transposed ...
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test2.gds' (2.5K)
    # of fragments: 41
    save to 'test2.gds.tmp'
    rename 'test2.gds.tmp' (2.2K, reduced: 333B)
    # of fragments: 20
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test2.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in individual-major mode (SNP X Sample).
VCF Format ==> SNP GDS Format
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
SNP genotypes: 3 samples, 5 SNPs
Genotype matrix is being transposed ...
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test3.gds' (2.6K)
    # of fragments: 41
    save to 'test3.gds.tmp'
    rename 'test3.gds.tmp' (2.3K, reduced: 335B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test3.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in individual-major mode (SNP X Sample).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
VCF Format ==> SNP GDS Format
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test4.gds' (2.5K)
    # of fragments: 39
    save to 'test4.gds.tmp'
    rename 'test4.gds.tmp' (2.3K, reduced: 228B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test4.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
VCF Format ==> SNP GDS Format
Method: dosage (0,1,2) of reference allele for all variant sites
Number of samples: 3
Parsing "/Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf" ...
	import 5 variants.
+ genotype   { Bit2 3x5, 4B } *
Optimize the access efficiency ...
Clean up the fragments of GDS file:
    open the file 'test5.gds' (2.5K)
    # of fragments: 39
    save to 'test5.gds.tmp'
    rename 'test5.gds.tmp' (2.3K, reduced: 228B)
    # of fragments: 20
Some of 'snp.allele' are not standard (e.g., T/A,G).
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test5.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
FUNCTION: snpgdsVCF2GDS_R
##fileformat=VCFv4.1
##fileDate=20090805
##source=myImputationProgramV3.1
##reference=file:///seq/references/1000GenomesPilot-NCBI36.fasta
##contig=<ID=20,length=62435964,assembly=B36,md5=f126cdf8a6e0c7f379d618ff66beb2da,species="Homo sapiens",taxonomy=x>
##phasing=partial
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of Samples With Data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency">
##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele">
##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP membership, build 129">
##INFO=<ID=H2,Number=0,Type=Flag,Description="HapMap2 membership">
##FILTER=<ID=q10,Description="Quality below 10">
##FILTER=<ID=s50,Description="Less than 50% of samples have data">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=HQ,Number=2,Type=Integer,Description="Haplotype Quality">
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	NA00001	NA00002	NA00003
20	14370	rs6054257	G	A	29	PASS	NS=3;DP=14;AF=0.5;DB;H2	GT:GQ:DP:HQ	0|0:48:1:51,51	1|0:48:8:51,51	1/1:43:5:.,.
20	17330	.	T	A	3	q10	NS=3;DP=11;AF=0.017	GT:GQ:DP:HQ	0|0:49:3:58,50	0|1:3:5:65,3	0/0:41:3
20	1110696	rs6040355	A	G,T	67	PASS	NS=2;DP=10;AF=0.333,0.667;AA=T;DB	GT:GQ:DP:HQ	1|2:21:6:23,27	2|1:2:0:18,2	2/2:35:4
20	1230237	.	T	.	47	PASS	NS=3;DP=13;AA=T	GT:GQ:DP:HQ	0|0:54:7:56,60	0|0:48:4:51,51	0/0:61:2
20	1234567	microsat1	GTC	G,GTCT	50	PASS	NS=3;DP=9;AA=G	GT:GQ:DP	0/1:35:4	0/2:17:2	1/1:40:3
Start snpgdsVCF2GDS ...
	Extracting bi-allelic and polymorhpic SNPs.
	Scanning ...
	file: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Thu Apr 12 09:50:17 2018 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 2 SNPs ...
	file: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf
[1] 1
Thu Apr 12 09:50:17 2018 	Done.
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test1.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Start snpgdsVCF2GDS ...
	Extracting bi-allelic and polymorhpic SNPs.
	Scanning ...
	file: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Thu Apr 12 09:50:17 2018 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 2 SNPs ...
	file: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf
[1] 1
Thu Apr 12 09:50:17 2018 	Done.
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test2.gds 
The total number of samples: 3 
The total number of SNPs: 2 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
Start snpgdsVCF2GDS ...
	Storing dosage of the reference allele for all variant sites, including bi-allelic SNPs, multi-allelic SNPs, indels and structural variants.
	Scanning ...
	file: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Thu Apr 12 09:50:17 2018 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 5 SNPs ...
	file: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf
Thu Apr 12 09:50:17 2018 	Done.
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test3.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
Start snpgdsVCF2GDS ...
	Storing dosage of the reference allele for all variant sites, including bi-allelic SNPs, multi-allelic SNPs, indels and structural variants.
	Scanning ...
	file: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf
	content: 5 rows x 12 columns
Thu Apr 12 09:50:17 2018 	store sample id, snp id, position, and chromosome.
	start writing: 3 samples, 5 SNPs ...
	file: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/SNPRelate/extdata/sequence.vcf
Thu Apr 12 09:50:17 2018 	Done.
Some of 'snp.allele' are not standard (e.g., A/G,T).
The file name: /Users/biocbuild/bbs-3.6-bioc/meat/SNPRelate.Rcheck/tests/test4.gds 
The total number of samples: 3 
The total number of SNPs: 5 
SNP genotypes are stored in SNP-major mode (Sample X SNP).
The number of valid samples: 3 
The number of biallelic unique SNPs: 2 
SNP Correlation:
Working space: 90 samples, 9088 SNPs
    using 1 (CPU) core
    using the top 2 eigenvectors
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Thu Apr 12 09:50:18 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:18 2018    Done.
SNP Correlation:
Working space: 90 samples, 9088 SNPs
    using 1 (CPU) core
    using the top 2 eigenvectors
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Thu Apr 12 09:50:18 2018

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:18 2018    Done.
SNP loading:
Working space: 90 samples, 8695 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 787449
Thu Apr 12 09:50:18 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:18 2018    Done.
Sample loading:
Working space: 100 samples, 8695 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 875255
Thu Apr 12 09:50:18 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:18 2018    Done.
SNP Correlation:
Working space: 90 samples, 9088 SNPs
    using 2 (CPU) cores
    using the top 2 eigenvectors
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Thu Apr 12 09:50:18 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:18 2018    Done.
SNP Correlation:
Working space: 90 samples, 9088 SNPs
    using 2 (CPU) cores
    using the top 2 eigenvectors
Creating 'test.gds' ...
Correlation:    the sum of all selected genotypes (0,1,2) = 824424
Thu Apr 12 09:50:18 2018

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:18 2018    Done.
SNP loading:
Working space: 90 samples, 8695 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
SNP Loading:    the sum of all selected genotypes (0,1,2) = 787449
Thu Apr 12 09:50:18 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:18 2018    Done.
Sample loading:
Working space: 100 samples, 8695 SNPs
    using 1 (CPU) core
    using the top 8 eigenvectors
Sample Loading:    the sum of all selected genotypes (0,1,2) = 875255
Thu Apr 12 09:50:18 2018    (internal increment: 65536)

[..................................................]  0%, ETC: ---    
[==================================================] 100%, completed in 0s
Thu Apr 12 09:50:18 2018    Done.


RUNIT TEST PROTOCOL -- Thu Apr 12 09:50:19 2018 
*********************************************** 
Number of test functions: 11 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
SNPRelate RUnit Tests - 11 test functions, 0 errors, 0 failures
Number of test functions: 11 
Number of errors: 0 
Number of failures: 0 
> 
> proc.time()
   user  system elapsed 
 33.750   1.305  35.780 

name	user	system	elapsed
SNPGDSFileClass-class	0.055	0.003	0.058
SNPRelate-package	1.726	0.070	1.838
snpgdsAdmixPlot	0.393	0.008	0.414
snpgdsAdmixProp	0.482	0.014	0.511
snpgdsAlleleSwitch	0.099	0.006	0.107
snpgdsApartSelection	0.145	0.008	0.155
snpgdsBED2GDS	0.218	0.009	0.232
snpgdsClose	0.017	0.001	0.017
snpgdsCombineGeno	0.567	0.025	0.597
snpgdsCreateGeno	0.250	0.014	0.277
snpgdsCreateGenoSet	0.163	0.010	0.184
snpgdsCutTree	2.263	0.049	2.381
snpgdsDiss	1.488	0.007	1.528
snpgdsDrawTree	1.468	0.007	1.509
snpgdsEIGMIX	0.319	0.012	0.335
snpgdsErrMsg	0.000	0.000	0.001
snpgdsExampleFileName	0.001	0.000	0.002
snpgdsFst	0.075	0.004	0.079
snpgdsGDS2BED	0.076	0.010	0.086
snpgdsGDS2Eigen	0.721	0.058	0.800
snpgdsGDS2PED	0.442	0.039	0.499
snpgdsGEN2GDS	0	0	0
snpgdsGRM	0.873	0.031	0.926
snpgdsGetGeno	0.278	0.012	0.292
snpgdsHCluster	1.758	0.022	1.826
snpgdsHWE	0.014	0.001	0.016
snpgdsIBDKING	0.487	0.009	0.513
snpgdsIBDMLE	0.754	0.010	0.789
snpgdsIBDMLELogLik	0.666	0.010	0.691
snpgdsIBDMoM	0.223	0.016	0.248
snpgdsIBDSelection	0.071	0.005	0.079
snpgdsIBS	0.340	0.008	0.353
snpgdsIBSNum	0.419	0.015	0.447
snpgdsIndInb	0.054	0.008	0.066
snpgdsIndInbCoef	0.037	0.001	0.045
snpgdsIndivBeta	0.277	0.007	0.291
snpgdsLDMat	0.401	0.017	0.424
snpgdsLDpair	0.019	0.002	0.021
snpgdsLDpruning	0.053	0.004	0.058
snpgdsMergeGRM	1.415	0.101	1.563
snpgdsOpen	0.016	0.001	0.017
snpgdsOption	0.004	0.001	0.005
snpgdsPCA	0.400	0.011	0.431
snpgdsPCACorr	0.491	0.028	0.531
snpgdsPCASNPLoading	0.384	0.013	0.413
snpgdsPCASampLoading	0.392	0.010	0.403
snpgdsPED2GDS	3.208	0.079	3.375
snpgdsPairIBD	1.046	0.014	1.097
snpgdsPairIBDMLELogLik	0.543	0.010	0.558
snpgdsPairScore	0.177	0.012	0.194
snpgdsSNPList	0.012	0.001	0.013
snpgdsSNPListIntersect	0.059	0.002	0.062
snpgdsSNPListStrand	0.053	0.002	0.056
snpgdsSNPRateFreq	0.022	0.003	0.025
snpgdsSampMissRate	0.007	0.001	0.007
snpgdsSelectSNP	0.007	0.001	0.008
snpgdsSlidingWindow	1.241	0.068	1.337
snpgdsSummary	0.224	0.002	0.231
snpgdsTranspose	0.150	0.010	0.162
snpgdsVCF2GDS	0.222	0.024	0.259
snpgdsVCF2GDS_R	0.233	0.009	0.244