Yingxin Lin
| Snapshot Date: 2024-05-06 14:00:02 -0400 (Mon, 06 May 2024) |
| git_url: https://git.bioconductor.org/packages/scMerge |
| git_branch: RELEASE_3_19 |
| git_last_commit: 0b5d058 |
| git_last_commit_date: 2024-04-30 11:14:29 -0400 (Tue, 30 Apr 2024) |
| Back to Mac ARM64 build report for BioC 3.19 |
|
This page was generated on 2024-05-07 11:32:44 -0400 (Tue, 07 May 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| kjohnson3 | macOS 13.6.5 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4461 |
| 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 1900/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| scMerge 1.20.0 (landing page) Yingxin Lin
| kjohnson3 | macOS 13.6.5 Ventura / arm64 | OK | OK | OK | OK | | |||||||
|
To the developers/maintainers of the scMerge package: - 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. |
| Package: scMerge |
| Version: 1.20.0 |
| 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_1.20.0.tar.gz |
| StartedAt: 2024-05-07 00:44:19 -0400 (Tue, 07 May 2024) |
| EndedAt: 2024-05-07 00:47:03 -0400 (Tue, 07 May 2024) |
| EllapsedTime: 163.8 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: scMerge.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### 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_1.20.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.19-bioc-mac-arm64/meat/scMerge.Rcheck’
* using R version 4.4.0 (2024-04-24)
* using platform: aarch64-apple-darwin20
* R was compiled by
Apple clang version 14.0.0 (clang-1400.0.29.202)
GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.5
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘scMerge/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘scMerge’ version ‘1.20.0’
* 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 code 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 ... NOTE
checkRd: (-1) scMerge.Rd:85: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) scMerge.Rd:86: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) scMerge2.Rd:82: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) scMerge2.Rd:83: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) scMerge2.Rd:84: Lost braces in \itemize; \value handles \item{}{} directly
* 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
scMerge2h 5.142 0.14 5.287
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘testthat.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... 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-3.19-bioc-mac-arm64/meat/scMerge.Rcheck/00check.log’
for details.
scMerge.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL scMerge ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-arm64/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)
scMerge.Rcheck/tests/testthat.Rout
R version 4.4.0 (2024-04-24) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20
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] 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 2 2 2
6 3 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"
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 3 2 1
5 2 2 2
6 1 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 1 1 2
3 2 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 3 1 2
3 1 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 1 1 1
2 2 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
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 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
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 1 1 1
2 2 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 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
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 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
Selecting optimal RUVk
No cell type info, replicate matrix will be used as cell type info
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[ FAIL 0 | WARN 85 | SKIP 0 | PASS 42 ]
[ FAIL 0 | WARN 85 | SKIP 0 | PASS 42 ]
>
> proc.time()
user system elapsed
49.396 1.263 50.543
scMerge.Rcheck/scMerge-Ex.timings
| name | user | system | elapsed | |
| fastRUVIII | 0.765 | 0.010 | 0.780 | |
| getAdjustedMat | 2.088 | 0.054 | 2.142 | |
| ruvSimulate | 0.971 | 0.031 | 1.002 | |
| scMerge | 0.740 | 0.030 | 0.769 | |
| scMerge2 | 1.168 | 0.032 | 1.201 | |
| scMerge2h | 5.142 | 0.140 | 5.287 | |
| scRUVIII | 0.622 | 0.027 | 0.649 | |
| scRUVg | 0.011 | 0.001 | 0.011 | |
| scReplicate | 0.141 | 0.005 | 0.147 | |
| scSEGIndex | 2.345 | 2.016 | 3.373 | |
| sce_cbind | 0.212 | 0.015 | 0.227 | |