Back to Multiple platform build/check report for BioC 3.17:   simplified   long
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This page was generated on 2023-10-16 11:37:30 -0400 (Mon, 16 Oct 2023).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.2 LTS)x86_644.3.1 (2023-06-16) -- "Beagle Scouts" 4626
palomino3Windows Server 2022 Datacenterx644.3.1 (2023-06-16 ucrt) -- "Beagle Scouts" 4379
merida1macOS 12.6.4 Montereyx86_644.3.1 (2023-06-16) -- "Beagle Scouts" 4395
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

Package 1844/2230HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
scMerge 1.16.0  (landing page)
Yingxin Lin
Snapshot Date: 2023-10-15 14:00:13 -0400 (Sun, 15 Oct 2023)
git_url: https://git.bioconductor.org/packages/scMerge
git_branch: RELEASE_3_17
git_last_commit: 33d1a0b
git_last_commit_date: 2023-04-25 11:09:58 -0400 (Tue, 25 Apr 2023)
nebbiolo1Linux (Ubuntu 22.04.2 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino3Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.6.4 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson2macOS 12.6.1 Monterey / arm64see weekly results here

CHECK results for scMerge on merida1


To the developers/maintainers of the scMerge package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/scMerge.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.

raw results


Summary

Package: scMerge
Version: 1.16.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:scMerge.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings scMerge_1.16.0.tar.gz
StartedAt: 2023-10-16 06:44:05 -0400 (Mon, 16 Oct 2023)
EndedAt: 2023-10-16 07:00:39 -0400 (Mon, 16 Oct 2023)
EllapsedTime: 994.3 seconds
RetCode: 0
Status:   OK  
CheckDir: scMerge.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:scMerge.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings scMerge_1.16.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.17-bioc/meat/scMerge.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: x86_64-apple-darwin20 (64-bit)
* R was compiled by
    Apple clang version 14.0.3 (clang-1403.0.22.14.1)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.6.4
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘scMerge/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘scMerge’ version ‘1.16.0’
* 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 ‘scMerge’ 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 files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                 user system elapsed
scSEGIndex      7.949  6.996  16.501
scMerge2h      12.999  0.502  24.411
getAdjustedMat  5.201  0.168   9.024
scMerge2        4.003  0.154   7.334
* 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


Installation output

scMerge.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL scMerge
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/library’
* installing *source* package ‘scMerge’ ...
** 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 (scMerge)

Tests output

scMerge.Rcheck/tests/testthat.Rout


R version 4.3.1 (2023-06-16) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (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(scMerge)
> 
> test_check("scMerge")
Dimension of the replicates mapping matrix: 
[1] 100   3
Dimension of the replicates mapping matrix: 
[1] 100   3
Dimension of the replicates mapping matrix: 
[1] 100   3
Dimension of the replicates mapping matrix: 
[1] 100   3
Dimension of the replicates mapping matrix: 
[1] 200   3
Dimension of the replicates mapping matrix: 
[1] 200   3
Dimension of the replicates mapping matrix: 
[1] 200   3
Dimension of the replicates mapping matrix: 
[1] 200   3
Dimension of the replicates mapping matrix: 
[1] 200   4
Dimension of the replicates mapping matrix: 
[1] 200   3
Selecting optimal RUVk 
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    75 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     3     1       1
2     1     1       2
3     2     1       3
4     1     2       1
5     3     2       2
6     2     2       3
Dimension of the replicates mapping matrix: 
[1] 200   3
Could not find a  batch  column in colData(sce_combine)[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   89
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   86
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047  100
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 1, data1"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   89
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 1, data2"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   86
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 2, data1"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047  100
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   89
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047  117
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 1, data1"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   89
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 2, data1"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047  117
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   50
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   50
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   50
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   50
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   86
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047  101
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 1, data1"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   50
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 1, data2"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   50
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 1, data3"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   50
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 1, data4"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   50
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 2, data1"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047   86
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
[1] "Hierarchical merging level 3, data1"
[1] "Cluster within batch"
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047  101
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
Selecting optimal RUVk 
No cell type info, replicate matrix will be used as cell type info 
Performing supervised scMerge with: 
 1. Cell type information 
 2. No cell type indices 
 3. No mutual nearest neighbour clustering 
Performing semi-supervised scMerge with: 
 1. Cell type information 
 2. No cell type indices 
 3. Mutual nearest neighbour clustering 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    75 HVG were found 
 5. Calculating supervised clustering list 
 6. Create Mutual Nearest Clusters. Preview cells-to-cell_type matching graph and matrix:
  group batch cluster
1     3     1       1
2     2     1       2
3     1     1       3
4     3     2       1
5     2     2       2
6     1     2       3
Performing semi-supervised scMerge with: 
 1. Cell type information 
 2. No cell type indices 
 3. Mutual nearest neighbour clustering 
 4. No supplied marker but supplied marker_list for MNN clustering 
    Taking the union of marker_list as the markers 
 5. Calculating supervised clustering list 
 6. Create Mutual Nearest Clusters. Preview cells-to-cell_type matching graph and matrix:
  group batch cluster
1     2     1       1
2     3     1       2
3     1     1       3
4     4     2       1
5     5     2       2
6     1     2       3
Performing semi-supervised scMerge with: 
 1. Cell type information 
 2. No cell type indices 
 3. Mutual nearest neighbour clustering 
 5. Calculating supervised clustering list 
 6. Create Mutual Nearest Clusters. Preview cells-to-cell_type matching graph and matrix:
  group batch cluster
1     2     1       1
2     3     1       2
3     1     1       3
4     4     2       1
5     5     2       2
6     1     2       3
Performing semi-supervised scMerge with: 
 1. Cell type information 
 2. No cell type indices 
 3. Mutual nearest neighbour clustering 
 5. Calculating supervised clustering list 
 6. Create Mutual Nearest Clusters. Preview cells-to-cell_type matching graph and matrix:
  group batch cluster
1     2     1       1
2     3     1       2
3     1     1       3
4     4     2       1
5     5     2       2
6     1     2       3
Performing semi-supervised scMerge with: 
 1. Cell type information 
 2. Cell type indices 
 3. No mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    75 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     3     1       1
2     2     1       2
3     1     1       3
4     1     2       1
5     3     2       2
6     2     2       3
 7. Finishing semi-supervised scMerge with subsets of known cell type 
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    75 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     3     1       1
2     2     1       2
3     1     1       3
4     1     2       1
5     3     2       2
6     2     2       3
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker but supplied marker_list for MNN clustering 
    Taking the union of marker_list as the markers 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     2     1       1
2     1     1       2
3     3     1       3
4     4     2       1
5     1     2       2
6     5     2       3
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     2     1       1
2     1     1       2
3     3     1       3
4     1     2       1
5     4     2       2
6     5     2       3
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    75 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     3     1       1
2     1     1       2
3     2     1       3
4     1     2       1
5     3     2       2
6     2     2       3
 7. Performing semi-supervised scMerge with wanted variation 
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    75 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     3     1       1
2     2     1       2
3     1     1       3
4     1     2       1
5     2     2       2
6     3     2       3
 7. Performing semi-supervised scMerge with wanted variation 
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    36 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     2     1       1
2     1     1       2
3     3     1       3
4     1     2       1
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    36 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     2     1       1
2     1     1       2
3     3     1       3
4     1     2       1
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    63 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     3     1       1
2     2     1       2
3     1     1       3
4     1     2       1
5     2     2       2
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    63 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     2     1       1
2     1     1       2
3     3     1       3
4     2     2       1
5     1     2       2
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    24 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     1     1       1
2     2     2       1
3     1     3       1
Performing unsupervised scMerge with: 
 1. No cell type information 
 2. Cell type indices not relevant here 
 3. Mutual nearest neighbour matching 
 4. No supplied marker and no supplied marker_list for MNN clustering 
    Finding Highly Variable Genes for clustering 
    24 HVG were found 
 5. PCA and Kmeans clustering will be performed on each batch 
 6. Create Mutual Nearest Clusters. Preview cells-cell_type matching output matrix: 
  group batch cluster
1     1     1       1
2     2     2       1
3     1     3       1

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[ FAIL 0 | WARN 84 | SKIP 0 | PASS 44 ]

[ FAIL 0 | WARN 84 | SKIP 0 | PASS 44 ]
> 
> proc.time()
   user  system elapsed 
156.050   6.262 266.674 

Example timings

scMerge.Rcheck/scMerge-Ex.timings

nameusersystemelapsed
fastRUVIII1.6290.0302.430
getAdjustedMat5.2010.1689.024
ruvSimulate1.9870.0744.325
scMerge2.3650.1294.085
scMerge24.0030.1547.334
scMerge2h12.999 0.50224.411
scRUVIII1.2600.1072.983
scRUVg0.0150.0010.018
scReplicate0.6160.0561.432
scSEGIndex 7.949 6.99616.501
sce_cbind1.1970.0662.587