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### Running command:
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### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:LineagePulse.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings LineagePulse_1.21.0.tar.gz
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* using log directory ‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/meat/LineagePulse.Rcheck’
* using R version 4.3.1 (2023-06-16)
* using platform: aarch64-apple-darwin20 (64-bit)
* 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 13.3.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘LineagePulse/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘LineagePulse’ version ‘1.21.0’
* 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 ‘LineagePulse’ can be installed ... WARNING
Found the following significant warnings:
Note: possible error in 'evalLogLikGeneMM(vecCounts = vecCounts, ': unused arguments (matDispParam = matDispParam, matDropParam = matDropParam, matWeights = matWeights)
Note: possible error in 'evalLogLikGeneMM(vecCounts = vecCounts, ': unused arguments (matDispParam = do.call(cbind, lapply(seq_len(ncol(matWeights)), function(m) vecDispParam)), matDropParam = do.call(cbind, lapply(seq_len(ncol(matWeights)), function(m) vecPiParam)), matWeights = matWeights)
See ‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/meat/LineagePulse.Rcheck/00install.out’ for details.
Information on the location(s) of code generating the ‘Note’s can be
obtained by re-running with environment variable R_KEEP_PKG_SOURCE set
to ‘yes’.
* 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 ... NOTE
decompressDispByGeneMM: no visible binding for global variable
‘lsDispModel’
evalLogLikMatrix : <anonymous>: possible error in
evalLogLikGeneMM(vecCounts = vecCounts, matMuParam = matMuParam,
vecNormConst = lsMuModel$lsMuModelGlobal$vecNormConst, matDispParam =
matDispParam, matDropParam = matDropParam, matWeights = matWeights,
vecidxNotZero = which(!is.na(vecCounts) & vecCounts > 0), vecidxZero
= which(!is.na(vecCounts) & vecCounts == 0), scaNCells =
length(vecCounts)): unused arguments (matDispParam = matDispParam,
matDropParam = matDropParam, matWeights = matWeights)
evalLogLikMatrix : <anonymous>: possible error in
evalLogLikGeneMM(vecCounts = vecCounts, matMuParam = do.call(cbind,
lapply(seq_len(ncol(matWeights)), function(m) vecMuParam)),
vecNormConst = lsMuModel$lsMuModelGlobal$vecNormConst, matDispParam =
do.call(cbind, lapply(seq_len(ncol(matWeights)), function(m)
vecDispParam)), matDropParam = do.call(cbind,
lapply(seq_len(ncol(matWeights)), function(m) vecPiParam)),
matWeights = matWeights, vecidxNotZero = which(!is.na(vecCounts) &
vecCounts > 0), vecidxZero = which(!is.na(vecCounts) & vecCounts ==
0), : unused arguments (matDispParam = do.call(cbind,
lapply(seq_len(ncol(matWeights)), function(m) vecDispParam)),
matDropParam = do.call(cbind, lapply(seq_len(ncol(matWeights)),
function(m) vecPiParam)), matWeights = matWeights)
evalLogLikMatrix : <anonymous>: possible error in scaNCells =
length(vecCounts)): unused arguments (matDispParam = do.call(cbind,
lapply(seq_len(ncol(matWeights)), function(m) vecDispParam)),
matDropParam = do.call(cbind, lapply(seq_len(ncol(matWeights)),
function(m) vecPiParam)), matWeights = matWeights)
plotCellDensity: no visible binding for global variable ‘continuous’
plotGene: no visible binding for global variable ‘x’
plotGene: no visible binding for global variable ‘dropout_posterior’
plotGene: no visible binding for global variable ‘groups’
plotGene: no visible binding for global variable ‘dfAnnot’
plotGene: no visible binding for global variable ‘mean_count’
plotGene: no visible binding for global variable ‘quantile_25’
plotGene: no visible binding for global variable ‘quantile_75’
plotGene: no visible binding for global variable ‘model’
plotGene: no visible binding for global variable ‘continuous’
plotGene: no visible binding for global variable ‘trajectory_contour’
plotGene: no visible binding for global variable ‘ncells’
Undefined global functions or variables:
continuous dfAnnot dropout_posterior groups lsDispModel mean_count
model ncells quantile_25 quantile_75 trajectory_contour x
* 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 ... ERROR
Running examples in ‘LineagePulse-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: plotGene
> ### Title: Plot counts and model for one gene
> ### Aliases: plotGene
>
> ### ** Examples
>
> lsSimulatedData <- simulateContinuousDataSet(
+ scaNCells = 100,
+ scaNConst = 10,
+ scaNLin = 10,
+ scaNImp = 10,
+ scaMumax = 100,
+ scaSDMuAmplitude = 3,
+ vecNormConstExternal=NULL,
+ vecDispExternal=rep(20, 30),
+ vecGeneWiseDropoutRates = rep(0.1, 30))
Draw mean trajectories
Setting size factors uniformly =1
Draw dispersion
Simulate negative binomial noise
Simulate drop-out
> matDropoutPredictors <- as.matrix(data.frame(
+ log_means = log(rowMeans(lsSimulatedData$counts)+1) ))
> objLP <- runLineagePulse(
+ counts = lsSimulatedData$counts,
+ dfAnnotation = lsSimulatedData$annot,
+ strMuModel = "splines", scaDFSplinesMu = 6,
+ strDropModel="logistic",
+ matPiConstPredictors = matDropoutPredictors)
LineagePulse for count data: v1.21.0
--- Data preprocessing
# 0 out of 100 cells did not have a continuous covariate and were excluded.
# 0 out of 30 genes did not contain non-zero observations and are excluded from analysis.
# 0 out of 100 cells did not contain non-zero observations and are excluded from analysis.
--- Compute normalisation constants:
# All size factors are set to one.
--- Fit ZINB model for both H1 and H0.
### a) Fit ZINB model A (H0: mu=constant disp=constant) with noise model.
# . Initialisation: ll -26573.7517367021
# 1. Iteration with ll -14605.5153293607 in 0.04 min.
# 2. Iteration with ll -14605.5153232726 in 0.03 min.
Finished fitting zero-inflated negative binomial model A with noise model in 0.1 min.
### b) Fit ZINB model B (H1: mu=splines disp=constant).
# . Initialisation: ll -15916.1276621442
# 1. Iteration with ll -13965.4265547435 in 0.03 min.
Finished fitting zero-inflated negative binomial model B in 0.04 min.
### c) Fit NB model A (H0: mu=constant disp=constant).
# . Initialisation: ll -15714.0124100307
# 1. Iteration with ll -15568.8432658988 in 0.02 min.
Finished fitting NB model B in 0.03 min.
### d) Fit NB model B (H1: mu=splines disp=constant).
# . Initialisation: ll -15928.4087901142
# 1. Iteration with ll -15439.6256630045 in 0.02 min.
Finished fitting NB model B in 0.04 min.
Time elapsed during ZINB fitting: 0.26 min
--- Run differential expression analysis.
Finished runLineagePulse().
> gplotExprProfile <- plotGene(
+ objLP = objLP,
+ strGeneID = rownames(lsSimulatedData$counts)[1],
+ boolLineageContour = FALSE)
Error in matCountsProc(objLP)[strGeneID, , sparse = FALSE] :
incorrect number of dimensions
Calls: plotGene -> [ -> [
Execution halted
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 ERROR, 1 WARNING, 1 NOTE
See
‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/meat/LineagePulse.Rcheck/00check.log’
for details.