António Sousa
| Snapshot Date: 2026-05-06 13:40 -0400 (Wed, 06 May 2026) |
| git_url: https://git.bioconductor.org/packages/Coralysis |
| git_branch: RELEASE_3_23 |
| git_last_commit: 24c1814 |
| git_last_commit_date: 2026-04-28 09:05:04 -0400 (Tue, 28 Apr 2026) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-05-07 11:36 -0400 (Thu, 07 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4990 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.6.0 Patched (2026-04-24 r89963) -- "Because it was There" | 4723 |
| 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 456/2418 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| Coralysis 1.2.0 (landing page) António Sousa
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | WARNINGS | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
| See other builds for Coralysis in R Universe. | ||||||||||||||
|
To the developers/maintainers of the Coralysis package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/Coralysis.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: Coralysis |
| Version: 1.2.0 |
| Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:Coralysis.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings Coralysis_1.2.0.tar.gz |
| StartedAt: 2026-05-06 19:34:22 -0400 (Wed, 06 May 2026) |
| EndedAt: 2026-05-06 19:36:48 -0400 (Wed, 06 May 2026) |
| EllapsedTime: 146.7 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: Coralysis.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:Coralysis.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings Coralysis_1.2.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.23-bioc/meat/Coralysis.Rcheck’
* using R version 4.6.0 Patched (2026-04-24 r89963)
* using platform: aarch64-apple-darwin23
* R was compiled by
Apple clang version 17.0.0 (clang-1700.3.19.1)
GNU Fortran (GCC) 14.2.0
* running under: macOS Tahoe 26.3.1
* using session charset: UTF-8
* current time: 2026-05-06 23:34:22 UTC
* using option ‘--no-vignettes’
* checking for file ‘Coralysis/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘Coralysis’ version ‘1.2.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... INFO
Imports includes 30 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable. Move as many as possible to Suggests and
use conditionally.
* 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 ‘Coralysis’ 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 ... NOTE
Namespace in Imports field not imported from: ‘utils’
All declared Imports should be used.
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
PlotDimRed: no visible global function definition for ‘tail’
PlotExpression: no visible global function definition for ‘tail’
PlotDimRed,SingleCellExperiment: no visible global function definition
for ‘tail’
PlotExpression,SingleCellExperiment: no visible global function
definition for ‘tail’
Undefined global functions or variables:
tail
Consider adding
importFrom("utils", "tail")
to your NAMESPACE file.
* 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 files in ‘vignettes’ ... OK
* checking examples ... WARNING
Found the following significant warnings:
Warning in getTopHVGs(b, n = nhvg) : 'getTopHVGs' is deprecated.
Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
Warning in getTopHVGs(b, n = nhvg) : 'getTopHVGs' is deprecated.
Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
Warning in getTopHVGs(b, n = nhvg) : 'getTopHVGs' is deprecated.
Warning in fitTrendVar(fm, fv, ...) : 'fitTrendVar' is deprecated.
Deprecated functions may be defunct as soon as of the next release of
R.
See ?Deprecated.
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
AggregateDataByBatch 10.087 0.287 18.059
* 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 WARNING, 2 NOTEs
See
‘/Users/biocbuild/bbs-3.23-bioc/meat/Coralysis.Rcheck/00check.log’
for details.
Coralysis.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL Coralysis ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.6/Resources/library’ * installing *source* package ‘Coralysis’ ... ** this is package ‘Coralysis’ version ‘1.2.0’ ** using staged installation ** R ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices *** copying figures ** 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 (Coralysis)
Coralysis.Rcheck/tests/testthat.Rout
R version 4.6.0 Patched (2026-04-24 r89963) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin23
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.
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(Coralysis)
>
> test_check("Coralysis")
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
WARNING: Setting 'divisive.method' to 'cluster' as 'batch.label=NULL'.
If 'batch.label=NULL', 'divisive.method' can be one of: 'cluster', 'random'.
Initializing divisive ICP clustering...
|
| | 0%
|
|=== | 4%
|
|====== | 8%
|
|======== | 12%
|
|=========== | 16%
|
|============== | 20%
|
|================= | 24%
|
|==================== | 28%
|
|====================== | 32%
|
|========================= | 36%
|
|============================ | 40%
|
|=============================== | 44%
|
|================================== | 48%
|
|==================================== | 52%
|
|======================================= | 56%
|
|========================================== | 60%
|
|============================================= | 64%
|
|================================================ | 68%
|
|================================================== | 72%
|
|===================================================== | 76%
|
|======================================================== | 80%
|
|=========================================================== | 84%
|
|============================================================== | 88%
|
|================================================================ | 92%
|
|=================================================================== | 96%
|
|======================================================================| 100%
Divisive ICP clustering completed successfully.
Predicting cell cluster probabilities using ICP models...
Prediction of cell cluster probabilities completed successfully.
Multi-level integration completed successfully.
Divisive ICP: selecting ICP tables multiple of 1
WARNING: Setting 'divisive.method' to 'cluster' as 'batch.label=NULL'.
If 'batch.label=NULL', 'divisive.method' can be one of: 'cluster', 'random'.
Initializing divisive ICP clustering...
|
| | 0%
|
|=== | 4%
|
|====== | 8%
|
|======== | 12%
|
|=========== | 16%
|
|============== | 20%
|
|================= | 24%
|
|==================== | 28%
|
|====================== | 32%
|
|========================= | 36%
|
|============================ | 40%
|
|=============================== | 44%
|
|================================== | 48%
|
|==================================== | 52%
|
|======================================= | 56%
|
|========================================== | 60%
|
|============================================= | 64%
|
|================================================ | 68%
|
|================================================== | 72%
|
|===================================================== | 76%
|
|======================================================== | 80%
|
|=========================================================== | 84%
|
|============================================================== | 88%
|
|================================================================ | 92%
|
|=================================================================== | 96%
|
|======================================================================| 100%
Divisive ICP clustering completed successfully.
Predicting cell cluster probabilities using ICP models...
Prediction of cell cluster probabilities completed successfully.
Multi-level integration completed successfully.
Divisive ICP: selecting ICP tables multiple of 1
Initializing divisive ICP clustering...
|
| | 0%
|
|=== | 4%
|
|====== | 8%
|
|======== | 12%
|
|=========== | 16%
|
|============== | 20%
|
|================= | 24%
|
|==================== | 28%
|
|====================== | 32%
|
|========================= | 36%
|
|============================ | 40%
|
|=============================== | 44%
|
|================================== | 48%
|
|==================================== | 52%
|
|======================================= | 56%
|
|========================================== | 60%
|
|============================================= | 64%
|
|================================================ | 68%
|
|================================================== | 72%
|
|===================================================== | 76%
|
|======================================================== | 80%
|
|=========================================================== | 84%
|
|============================================================== | 88%
|
|================================================================ | 92%
|
|=================================================================== | 96%
|
|======================================================================| 100%
Divisive ICP clustering completed successfully.
Predicting cell cluster probabilities using ICP models...
Prediction of cell cluster probabilities completed successfully.
Multi-level integration completed successfully.
Parallelism disabled, because threads = 1
Initializing divisive ICP clustering...
ICP run: 1
ICP run: 2
ICP run: 3
ICP run: 4
ICP run: 5
ICP run: 6
ICP run: 7
ICP run: 8
ICP run: 9
ICP run: 10
ICP run: 11
ICP run: 12
ICP run: 13
ICP run: 14
ICP run: 15
ICP run: 16
ICP run: 17
ICP run: 18
ICP run: 19
ICP run: 20
ICP run: 21
ICP run: 22
ICP run: 23
ICP run: 24
ICP run: 25
Divisive ICP clustering completed successfully.
Predicting cell cluster probabilities using ICP models...
Prediction of cell cluster probabilities completed successfully.
Multi-level integration completed successfully.
Initializing divisive ICP clustering...
|
| | 0%
|
|======= | 10%
|
|============== | 20%
|
|===================== | 30%
|
|============================ | 40%
|
|=================================== | 50%
|
|========================================== | 60%
|
|================================================= | 70%
|
|======================================================== | 80%
|
|=============================================================== | 90%
|
|======================================================================| 100%
Divisive ICP clustering completed successfully.
Predicting cell cluster probabilities using ICP models...
Prediction of cell cluster probabilities completed successfully.
Multi-level integration completed successfully.
WARNING: Setting 'divisive.method' to 'cluster' as 'batch.label=NULL'.
If 'batch.label=NULL', 'divisive.method' can be one of: 'cluster', 'random'.
Initializing divisive ICP clustering...
|
| | 0%
|
|=== | 4%
|
|====== | 8%
|
|======== | 12%
|
|=========== | 16%
|
|============== | 20%
|
|================= | 24%
|
|==================== | 28%
|
|====================== | 32%
|
|========================= | 36%
|
|============================ | 40%
|
|=============================== | 44%
|
|================================== | 48%
|
|==================================== | 52%
|
|======================================= | 56%
|
|========================================== | 60%
|
|============================================= | 64%
|
|================================================ | 68%
|
|================================================== | 72%
|
|===================================================== | 76%
|
|======================================================== | 80%
|
|=========================================================== | 84%
|
|============================================================== | 88%
|
|================================================================ | 92%
|
|=================================================================== | 96%
|
|======================================================================| 100%
Divisive ICP clustering completed successfully.
Predicting cell cluster probabilities using ICP models...
Prediction of cell cluster probabilities completed successfully.
Multi-level integration completed successfully.
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 11 ]
>
> proc.time()
user system elapsed
14.929 5.708 14.335
Coralysis.Rcheck/Coralysis-Ex.timings
| name | user | system | elapsed | |
| AggregateDataByBatch | 10.087 | 0.287 | 18.059 | |
| BinCellClusterProbability | 0 | 0 | 0 | |
| CellBinsFeatureCorrelation | 0 | 0 | 0 | |
| CellClusterProbabilityDistribution | 2.506 | 1.628 | 2.479 | |
| FindAllClusterMarkers | 0.086 | 0.013 | 0.100 | |
| FindClusterMarkers | 0.091 | 0.010 | 0.102 | |
| GetCellClusterProbability | 1.421 | 1.355 | 1.688 | |
| GetFeatureCoefficients | 2.253 | 1.569 | 2.217 | |
| HeatmapFeatures | 0.138 | 0.033 | 0.172 | |
| MajorityVotingFeatures | 0 | 0 | 0 | |
| PCAElbowPlot | 2.117 | 1.589 | 2.447 | |
| PlotClusterTree | 2.724 | 1.746 | 2.803 | |
| PlotDimRed | 0.672 | 0.031 | 0.715 | |
| PlotExpression | 0.622 | 0.009 | 0.631 | |
| PrepareData | 0.103 | 0.005 | 0.108 | |
| ReferenceMapping | 2.077 | 1.165 | 2.416 | |
| RunPCA | 1.949 | 1.607 | 2.256 | |
| RunParallelDivisiveICP | 1.968 | 1.558 | 2.266 | |
| RunTSNE | 0.661 | 0.020 | 0.687 | |
| RunUMAP | 2.599 | 1.620 | 2.982 | |
| SummariseCellClusterProbability | 2.005 | 1.575 | 2.362 | |
| TabulateCellBinsByGroup | 0 | 0 | 0 | |
| VlnPlot | 0.525 | 0.023 | 0.548 | |