Yingxin Lin
| Snapshot Date: 2025-10-10 13:45 -0400 (Fri, 10 Oct 2025) |
| git_url: https://git.bioconductor.org/packages/scMerge |
| git_branch: devel |
| git_last_commit: a277f5a |
| git_last_commit_date: 2025-04-15 11:44:10 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-10-11 12:03 -0400 (Sat, 11 Oct 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4864 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4652 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4597 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4586 |
| 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 1921/2346 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| scMerge 1.25.0 (landing page) Yingxin Lin
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | ERROR | |||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | ERROR | skipped | ||||||||||
|
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. |
| Package: scMerge |
| Version: 1.25.0 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:scMerge.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings scMerge_1.25.0.tar.gz |
| StartedAt: 2025-10-11 04:12:36 -0400 (Sat, 11 Oct 2025) |
| EndedAt: 2025-10-11 04:20:44 -0400 (Sat, 11 Oct 2025) |
| EllapsedTime: 488.4 seconds |
| RetCode: 1 |
| Status: ERROR |
| CheckDir: scMerge.Rcheck |
| Warnings: NA |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:scMerge.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings scMerge_1.25.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/scMerge.Rcheck’
* using R version 4.5.1 Patched (2025-08-23 r88802)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘scMerge/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘scMerge’ version ‘1.25.0’
* 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 loading without being on the library search path ... 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 ... ERROR
Running examples in ‘scMerge-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: getAdjustedMat
> ### Title: getAdjustedMat
> ### Aliases: getAdjustedMat
>
> ### ** Examples
>
> ## Loading example data
> data('example_sce', package = 'scMerge')
> ## Previously computed stably expressed genes
> data('segList_ensemblGeneID', package = 'scMerge')
> ## Running an example data with minimal inputs
> library(SingleCellExperiment)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats
Attaching package: ‘MatrixGenerics’
The following objects are masked from ‘package:matrixStats’:
colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
colWeightedMeans, colWeightedMedians, colWeightedSds,
colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
rowWeightedSds, rowWeightedVars
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: generics
Attaching package: ‘generics’
The following objects are masked from ‘package:base’:
as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
setequal, union
Attaching package: ‘BiocGenerics’
The following objects are masked from ‘package:stats’:
IQR, mad, sd, var, xtabs
The following objects are masked from ‘package:base’:
Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,
mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,
unsplit, which.max, which.min
Loading required package: S4Vectors
Attaching package: ‘S4Vectors’
The following object is masked from ‘package:utils’:
findMatches
The following objects are masked from ‘package:base’:
I, expand.grid, unname
Loading required package: IRanges
Loading required package: Seqinfo
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: ‘Biobase’
The following object is masked from ‘package:MatrixGenerics’:
rowMedians
The following objects are masked from ‘package:matrixStats’:
anyMissing, rowMedians
> scMerge2_res <- scMerge2(exprsMat = logcounts(example_sce),
+ batch = example_sce$batch,
+ ctl = segList_ensemblGeneID$mouse$mouse_scSEG,
+ return_matrix = FALSE)
[1] "Cluster within batch"
Warning in (function (A, nv = 5, nu = nv, maxit = 1000, work = nv + 7, reorth = TRUE, :
You're computing too large a percentage of total singular values, use a standard svd instead.
Warning in (function (A, nv = 5, nu = nv, maxit = 1000, work = nv + 7, reorth = TRUE, :
You're computing too large a percentage of total singular values, use a standard svd instead.
[1] "Normalising data"
[1] "Constructing pseudo-bulk"
Dimension of pseudo-bulk expression: [1] 1047 131
[1] "Identifying MNC using pseudo-bulk:"
[1] "Running RUV"
> cosineNorm_mat <- batchelor::cosineNorm(logcounts(example_sce))
> adjusted_means <- DelayedMatrixStats::rowMeans2(cosineNorm_mat)
> newY <- getAdjustedMat(cosineNorm_mat, scMerge2_res$fullalpha,
+ ctl = segList_ensemblGeneID$mouse$mouse_scSEG,
+ ruvK = 20,
+ adjusted_means = adjusted_means)
> assay(example_sce, "scMerge2") <- newY
>
> example_sce = scater::runPCA(example_sce, exprs_values = 'scMerge2')
Loading required namespace: GenomeInfoDb
Failed with error: ‘there is no package called ‘GenomeInfoDb’’
Error in .requirePackage(package) :
unable to load required package ‘GenomeInfoDb’
Calls: <Anonymous> ... .extendsForS3 -> extends -> getClassDef -> .requirePackage
Execution halted
* 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 re-building of vignette outputs ... ERROR
Error(s) in re-building vignettes:
--- re-building ‘scMerge.Rmd’ using rmarkdown
Failed with error: 'there is no package called 'GenomeInfoDb''
Quitting from scMerge.Rmd:107-114 [checking raw data]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `.requirePackage()`:
! unable to load required package 'GenomeInfoDb'
---
Backtrace:
▆
1. ├─BiocSingular::runPCA(example_sce, exprs_values = "logcounts")
2. ├─scater::runPCA(example_sce, exprs_values = "logcounts")
3. │ └─scater (local) .local(x, ...)
4. │ ├─SingleCellExperiment::`reducedDim<-`(`*tmp*`, name, value = `<dbl[,50]>`)
5. │ └─SingleCellExperiment::`reducedDim<-`(`*tmp*`, name, value = `<dbl[,50]>`)
6. │ └─SingleCellExperiment:::.set_internal_character(...)
7. │ ├─BiocGenerics::updateObject(x)
8. │ └─SingleCellExperiment::updateObject(x)
9. │ ├─methods::callNextMethod()
10. │ └─SummarizedExperiment (local) .nextMethod(object = object)
11. │ ├─BiocGenerics::updateObject(object@rowRanges, ..., verbose = verbose)
12. │ └─GenomicRanges::updateObject(object@rowRanges, ..., verbose = verbose)
13. │ ├─BiocGenerics::updateObject(object@unlistData, ..., verbose = verbose)
14. │ └─GenomicRanges::updateObject(object@unlistData, ..., verbose = verbose)
15. │ └─BiocGenerics::updateObject(object@seqinfo, ..., verbose = verbose)
16. └─methods:::.extendsForS3(`<chr>`)
17. └─methods::extends(Class, maybe = FALSE)
18. └─methods::getClassDef(class1)
19. └─methods:::.requirePackage(package)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'scMerge.Rmd' failed with diagnostics:
unable to load required package 'GenomeInfoDb'
--- failed re-building ‘scMerge.Rmd’
--- re-building ‘scMerge2.Rmd’ using rmarkdown
Failed with error: 'there is no package called 'GenomeInfoDb''
Quitting from scMerge2.Rmd:65-71 [checking raw data]
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<error/rlang_error>
Error in `.requirePackage()`:
! unable to load required package 'GenomeInfoDb'
---
Backtrace:
▆
1. ├─BiocSingular::runPCA(example_sce, exprs_values = "logcounts")
2. ├─scater::runPCA(example_sce, exprs_values = "logcounts")
3. │ └─scater (local) .local(x, ...)
4. │ ├─SingleCellExperiment::`reducedDim<-`(`*tmp*`, name, value = `<dbl[,50]>`)
5. │ └─SingleCellExperiment::`reducedDim<-`(`*tmp*`, name, value = `<dbl[,50]>`)
6. │ └─SingleCellExperiment:::.set_internal_character(...)
7. │ ├─BiocGenerics::updateObject(x)
8. │ └─SingleCellExperiment::updateObject(x)
9. │ ├─methods::callNextMethod()
10. │ └─SummarizedExperiment (local) .nextMethod(object = object)
11. │ ├─BiocGenerics::updateObject(object@rowRanges, ..., verbose = verbose)
12. │ └─GenomicRanges::updateObject(object@rowRanges, ..., verbose = verbose)
13. │ ├─BiocGenerics::updateObject(object@unlistData, ..., verbose = verbose)
14. │ └─GenomicRanges::updateObject(object@unlistData, ..., verbose = verbose)
15. │ └─BiocGenerics::updateObject(object@seqinfo, ..., verbose = verbose)
16. └─methods:::.extendsForS3(`<chr>`)
17. └─methods::extends(Class, maybe = FALSE)
18. └─methods::getClassDef(class1)
19. └─methods:::.requirePackage(package)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Error: processing vignette 'scMerge2.Rmd' failed with diagnostics:
unable to load required package 'GenomeInfoDb'
--- failed re-building ‘scMerge2.Rmd’
SUMMARY: processing the following files failed:
‘scMerge.Rmd’ ‘scMerge2.Rmd’
Error: Vignette re-building failed.
Execution halted
* checking PDF version of manual ... OK
* DONE
Status: 2 ERRORs, 1 NOTE
See
‘/home/biocbuild/bbs-3.22-bioc/meat/scMerge.Rcheck/00check.log’
for details.
scMerge.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL scMerge ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’ * installing *source* package ‘scMerge’ ... ** this is package ‘scMerge’ version ‘1.25.0’ ** 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 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
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"
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 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 3 2 1
5 2 2 2
6 1 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 1 1 1
2 2 1 2
3 3 1 3
4 4 2 1
5 5 2 2
6 1 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 4 2 1
5 5 2 2
6 1 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 3 2 1
5 2 2 2
6 1 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 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
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 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 85 | SKIP 0 | PASS 42 ]
[ FAIL 0 | WARN 85 | SKIP 0 | PASS 42 ]
>
> proc.time()
user system elapsed
149.023 1.514 150.596
scMerge.Rcheck/scMerge-Ex.timings
| name | user | system | elapsed | |
| fastRUVIII | 1.636 | 0.090 | 1.726 | |