##############################################################################
##############################################################################
###
### Running command:
###
### C:\Users\biocbuild\bbs-3.12-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:ImpulseDE2.install-out.txt --library=C:\Users\biocbuild\bbs-3.12-bioc\R\library --no-vignettes --timings ImpulseDE2_1.14.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'C:/Users/biocbuild/bbs-3.12-bioc/meat/ImpulseDE2.Rcheck'
* using R version 4.0.5 (2021-03-31)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* using option '--no-vignettes'
* checking for file 'ImpulseDE2/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'ImpulseDE2' version '1.14.0'
* 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 whether package 'ImpulseDE2' can be installed ... WARNING
Found the following significant warnings:
Warning: Package 'ImpulseDE2' is deprecated and will be removed from
See 'C:/Users/biocbuild/bbs-3.12-bioc/meat/ImpulseDE2.Rcheck/00install.out' for details.
* 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
* loading checks for arch 'i386'
** 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
* loading checks for arch 'x64'
** 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
plotGenes: no visible global function definition for 'error'
plotGenes: no visible binding for global variable 'normCounts'
plotGenes: no visible binding for global variable 'Condition'
plotGenes: no visible binding for global variable 'Batch'
plotGenes: no visible binding for global variable 'value'
plotGenes: no visible binding for global variable 'BatchFit'
Undefined global functions or variables:
Batch BatchFit Condition error normCounts value
* 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 ...
** running examples for arch 'i386' ... ERROR
Running examples in 'ImpulseDE2-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: fitSigmoidModels
> ### Title: Fits sigmoidal models to all genes on all all samples of a
> ### condition
> ### Aliases: fitSigmoidModels
>
> ### ** Examples
>
> lsSimulatedData <- simulateDataSetImpulseDE2(
+ vecTimePointsA = rep(seq(1,8),3),
+ vecTimePointsB = NULL,
+ vecBatchesA = NULL,
+ vecBatchesB = NULL,
+ scaNConst = 0,
+ scaNImp = 20,
+ scaNLin = 10,
+ scaNSig = 20)
[1] "Setting no batch structure."
> objectImpulseDE2 <- runImpulseDE2(
+ matCountData = lsSimulatedData$matObservedCounts,
+ dfAnnotation = lsSimulatedData$dfAnnotation,
+ boolCaseCtrl = FALSE,
+ vecConfounders = NULL,
+ boolIdentifyTransients = FALSE,
+ scaNProc = 1 )
ImpulseDE2 for count data, v1.14.0
# Process input
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
ImpulseDE2
--- call from context ---
system.time({
strMessage <- "# Process input"
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
if (class(matCountData) == "SummarizedExperiment") {
matCountData <- assay(matCountData)
}
lsProcessedData <- processData(dfAnnotation = dfAnnotation,
matCountData = matCountData, boolCaseCtrl = boolCaseCtrl,
vecConfounders = vecConfounders, vecDispersionsExternal = vecDispersionsExternal,
vecSizeFactorsExternal = vecSizeFactorsExternal)
matCountDataProc <- lsProcessedData$matCountDataProc
dfAnnotationProc <- lsProcessedData$dfAnnotationProc
vecSizeFactorsExternalProc <- lsProcessedData$vecSizeFactorsExternalProc
vecDispersionsExternalProc <- lsProcessedData$vecDispersionsExternalProc
if (boolVerbose) {
write(lsProcessedData$strReportProcessing, file = "",
ncolumns = 1)
}
strReport <- paste0(strReport, lsProcessedData$strReportProcessing)
if (scaNProc > 1) {
register(MulticoreParam(workers = scaNProc))
}
else {
register(SerialParam())
}
if (is.null(vecDispersionsExternal)) {
strMessage <- paste0("# Run DESeq2: Using dispersion factors",
"computed by DESeq2.")
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
tm_runDESeq2 <- system.time({
vecDispersions <- runDESeq2(dfAnnotationProc = dfAnnotationProc,
matCountDataProc = matCountDataProc, boolCaseCtrl = boolCaseCtrl,
vecConfounders = vecConfounders)
})
strMessage <- paste0("Consumed time: ", round(tm_runDESeq2["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
}
else {
strMessage <- "# Using externally supplied dispersion factors."
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
vecDispersions <- vecDispersionsExternalProc
}
strMessage <- "# Compute size factors"
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
vecSizeFactors <- computeNormConst(matCountDataProc = matCountDataProc,
vecSizeFactorsExternal = vecSizeFactorsExternalProc)
objectImpulseDE2 <- new("ImpulseDE2Object", dfImpulseDE2Results = NULL,
vecDEGenes = NULL, lsModelFits = NULL, matCountDataProc = matCountDataProc,
vecAllIDs = rownames(matCountData), dfAnnotationProc = dfAnnotationProc,
vecSizeFactors = vecSizeFactors, vecDispersions = vecDispersions,
boolCaseCtrl = boolCaseCtrl, vecConfounders = vecConfounders,
scaNProc = scaNProc, scaQThres = scaQThres, strReport = strReport)
strMessage <- "# Fitting null and alternative model to the genes"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
tm_fitImpulse <- system.time({
objectImpulseDE2 <- fitModels(objectImpulseDE2 = objectImpulseDE2,
vecConfounders = vecConfounders, boolCaseCtrl = boolCaseCtrl)
})
strMessage <- paste0("Consumed time: ", round(tm_fitImpulse["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
if (boolIdentifyTransients) {
strMessage <- "# Fitting sigmoid model to case condition"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
tm_fitSigmoid <- system.time({
objectImpulseDE2 <- fitSigmoidModels(objectImpulseDE2 = objectImpulseDE2,
vecConfounders = vecConfounders, strCondition = "case")
})
strMessage <- paste0("Consumed time: ", round(tm_fitSigmoid["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
}
strMessage <- "# Differentially expression analysis based on model fits"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
objectImpulseDE2 <- runDEAnalysis(objectImpulseDE2 = objectImpulseDE2,
boolCaseCtrl = get_boolCaseCtrl(obj = objectImpulseDE2),
boolIdentifyTransients = boolIdentifyTransients)
if (!is.null(scaQThres)) {
vecDEGenes <- as.vector(objectImpulseDE2$dfImpulseDE2Results[as.numeric(objectImpulseDE2$dfImpulseDE2Results$padj) <=
scaQThres, "Gene"])
strMessage <- paste0("Found ", length(vecDEGenes), " DE genes",
" at a FDR corrected p-value cut off of ", scaQThres,
".")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
}
else {
vecDEGenes <- NULL
}
objectImpulseDE2 <- set_vecDEGenes(obj = objectImpulseDE2,
element = vecDEGenes)
})
--- call from argument ---
if (class(matCountData) == "SummarizedExperiment") {
matCountData <- assay(matCountData)
}
--- R stacktrace ---
where 1: system.time({
strMessage <- "# Process input"
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
if (class(matCountData) == "SummarizedExperiment") {
matCountData <- assay(matCountData)
}
lsProcessedData <- processData(dfAnnotation = dfAnnotation,
matCountData = matCountData, boolCaseCtrl = boolCaseCtrl,
vecConfounders = vecConfounders, vecDispersionsExternal = vecDispersionsExternal,
vecSizeFactorsExternal = vecSizeFactorsExternal)
matCountDataProc <- lsProcessedData$matCountDataProc
dfAnnotationProc <- lsProcessedData$dfAnnotationProc
vecSizeFactorsExternalProc <- lsProcessedData$vecSizeFactorsExternalProc
vecDispersionsExternalProc <- lsProcessedData$vecDispersionsExternalProc
if (boolVerbose) {
write(lsProcessedData$strReportProcessing, file = "",
ncolumns = 1)
}
strReport <- paste0(strReport, lsProcessedData$strReportProcessing)
if (scaNProc > 1) {
register(MulticoreParam(workers = scaNProc))
}
else {
register(SerialParam())
}
if (is.null(vecDispersionsExternal)) {
strMessage <- paste0("# Run DESeq2: Using dispersion factors",
"computed by DESeq2.")
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
tm_runDESeq2 <- system.time({
vecDispersions <- runDESeq2(dfAnnotationProc = dfAnnotationProc,
matCountDataProc = matCountDataProc, boolCaseCtrl = boolCaseCtrl,
vecConfounders = vecConfounders)
})
strMessage <- paste0("Consumed time: ", round(tm_runDESeq2["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
}
else {
strMessage <- "# Using externally supplied dispersion factors."
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
vecDispersions <- vecDispersionsExternalProc
}
strMessage <- "# Compute size factors"
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
vecSizeFactors <- computeNormConst(matCountDataProc = matCountDataProc,
vecSizeFactorsExternal = vecSizeFactorsExternalProc)
objectImpulseDE2 <- new("ImpulseDE2Object", dfImpulseDE2Results = NULL,
vecDEGenes = NULL, lsModelFits = NULL, matCountDataProc = matCountDataProc,
vecAllIDs = rownames(matCountData), dfAnnotationProc = dfAnnotationProc,
vecSizeFactors = vecSizeFactors, vecDispersions = vecDispersions,
boolCaseCtrl = boolCaseCtrl, vecConfounders = vecConfounders,
scaNProc = scaNProc, scaQThres = scaQThres, strReport = strReport)
strMessage <- "# Fitting null and alternative model to the genes"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
tm_fitImpulse <- system.time({
objectImpulseDE2 <- fitModels(objectImpulseDE2 = objectImpulseDE2,
vecConfounders = vecConfounders, boolCaseCtrl = boolCaseCtrl)
})
strMessage <- paste0("Consumed time: ", round(tm_fitImpulse["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
if (boolIdentifyTransients) {
strMessage <- "# Fitting sigmoid model to case condition"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
tm_fitSigmoid <- system.time({
objectImpulseDE2 <- fitSigmoidModels(objectImpulseDE2 = objectImpulseDE2,
vecConfounders = vecConfounders, strCondition = "case")
})
strMessage <- paste0("Consumed time: ", round(tm_fitSigmoid["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
}
strMessage <- "# Differentially expression analysis based on model fits"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
objectImpulseDE2 <- runDEAnalysis(objectImpulseDE2 = objectImpulseDE2,
boolCaseCtrl = get_boolCaseCtrl(obj = objectImpulseDE2),
boolIdentifyTransients = boolIdentifyTransients)
if (!is.null(scaQThres)) {
vecDEGenes <- as.vector(objectImpulseDE2$dfImpulseDE2Results[as.numeric(objectImpulseDE2$dfImpulseDE2Results$padj) <=
scaQThres, "Gene"])
strMessage <- paste0("Found ", length(vecDEGenes), " DE genes",
" at a FDR corrected p-value cut off of ", scaQThres,
".")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
}
else {
vecDEGenes <- NULL
}
objectImpulseDE2 <- set_vecDEGenes(obj = objectImpulseDE2,
element = vecDEGenes)
})
where 2: runImpulseDE2(matCountData = lsSimulatedData$matObservedCounts,
dfAnnotation = lsSimulatedData$dfAnnotation, boolCaseCtrl = FALSE,
vecConfounders = NULL, boolIdentifyTransients = FALSE, scaNProc = 1)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (expr, gcFirst = TRUE)
{
ppt <- function(y) {
if (!is.na(y[4L]))
y[1L] <- y[1L] + y[4L]
if (!is.na(y[5L]))
y[2L] <- y[2L] + y[5L]
paste(formatC(y[1L:3L]), collapse = " ")
}
if (gcFirst)
gc(FALSE)
time <- proc.time()
on.exit(message("Timing stopped at: ", ppt(proc.time() -
time)))
expr
new.time <- proc.time()
on.exit()
structure(new.time - time, class = "proc_time")
}
<bytecode: 0x13415198>
<environment: namespace:base>
--- function search by body ---
Function system.time in namespace base has this body.
----------- END OF FAILURE REPORT --------------
Fatal error: the condition has length > 1
** running examples for arch 'x64' ... ERROR
Running examples in 'ImpulseDE2-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: fitSigmoidModels
> ### Title: Fits sigmoidal models to all genes on all all samples of a
> ### condition
> ### Aliases: fitSigmoidModels
>
> ### ** Examples
>
> lsSimulatedData <- simulateDataSetImpulseDE2(
+ vecTimePointsA = rep(seq(1,8),3),
+ vecTimePointsB = NULL,
+ vecBatchesA = NULL,
+ vecBatchesB = NULL,
+ scaNConst = 0,
+ scaNImp = 20,
+ scaNLin = 10,
+ scaNSig = 20)
[1] "Setting no batch structure."
> objectImpulseDE2 <- runImpulseDE2(
+ matCountData = lsSimulatedData$matObservedCounts,
+ dfAnnotation = lsSimulatedData$dfAnnotation,
+ boolCaseCtrl = FALSE,
+ vecConfounders = NULL,
+ boolIdentifyTransients = FALSE,
+ scaNProc = 1 )
ImpulseDE2 for count data, v1.14.0
# Process input
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
ImpulseDE2
--- call from context ---
system.time({
strMessage <- "# Process input"
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
if (class(matCountData) == "SummarizedExperiment") {
matCountData <- assay(matCountData)
}
lsProcessedData <- processData(dfAnnotation = dfAnnotation,
matCountData = matCountData, boolCaseCtrl = boolCaseCtrl,
vecConfounders = vecConfounders, vecDispersionsExternal = vecDispersionsExternal,
vecSizeFactorsExternal = vecSizeFactorsExternal)
matCountDataProc <- lsProcessedData$matCountDataProc
dfAnnotationProc <- lsProcessedData$dfAnnotationProc
vecSizeFactorsExternalProc <- lsProcessedData$vecSizeFactorsExternalProc
vecDispersionsExternalProc <- lsProcessedData$vecDispersionsExternalProc
if (boolVerbose) {
write(lsProcessedData$strReportProcessing, file = "",
ncolumns = 1)
}
strReport <- paste0(strReport, lsProcessedData$strReportProcessing)
if (scaNProc > 1) {
register(MulticoreParam(workers = scaNProc))
}
else {
register(SerialParam())
}
if (is.null(vecDispersionsExternal)) {
strMessage <- paste0("# Run DESeq2: Using dispersion factors",
"computed by DESeq2.")
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
tm_runDESeq2 <- system.time({
vecDispersions <- runDESeq2(dfAnnotationProc = dfAnnotationProc,
matCountDataProc = matCountDataProc, boolCaseCtrl = boolCaseCtrl,
vecConfounders = vecConfounders)
})
strMessage <- paste0("Consumed time: ", round(tm_runDESeq2["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
}
else {
strMessage <- "# Using externally supplied dispersion factors."
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
vecDispersions <- vecDispersionsExternalProc
}
strMessage <- "# Compute size factors"
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
vecSizeFactors <- computeNormConst(matCountDataProc = matCountDataProc,
vecSizeFactorsExternal = vecSizeFactorsExternalProc)
objectImpulseDE2 <- new("ImpulseDE2Object", dfImpulseDE2Results = NULL,
vecDEGenes = NULL, lsModelFits = NULL, matCountDataProc = matCountDataProc,
vecAllIDs = rownames(matCountData), dfAnnotationProc = dfAnnotationProc,
vecSizeFactors = vecSizeFactors, vecDispersions = vecDispersions,
boolCaseCtrl = boolCaseCtrl, vecConfounders = vecConfounders,
scaNProc = scaNProc, scaQThres = scaQThres, strReport = strReport)
strMessage <- "# Fitting null and alternative model to the genes"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
tm_fitImpulse <- system.time({
objectImpulseDE2 <- fitModels(objectImpulseDE2 = objectImpulseDE2,
vecConfounders = vecConfounders, boolCaseCtrl = boolCaseCtrl)
})
strMessage <- paste0("Consumed time: ", round(tm_fitImpulse["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
if (boolIdentifyTransients) {
strMessage <- "# Fitting sigmoid model to case condition"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
tm_fitSigmoid <- system.time({
objectImpulseDE2 <- fitSigmoidModels(objectImpulseDE2 = objectImpulseDE2,
vecConfounders = vecConfounders, strCondition = "case")
})
strMessage <- paste0("Consumed time: ", round(tm_fitSigmoid["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
}
strMessage <- "# Differentially expression analysis based on model fits"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
objectImpulseDE2 <- runDEAnalysis(objectImpulseDE2 = objectImpulseDE2,
boolCaseCtrl = get_boolCaseCtrl(obj = objectImpulseDE2),
boolIdentifyTransients = boolIdentifyTransients)
if (!is.null(scaQThres)) {
vecDEGenes <- as.vector(objectImpulseDE2$dfImpulseDE2Results[as.numeric(objectImpulseDE2$dfImpulseDE2Results$padj) <=
scaQThres, "Gene"])
strMessage <- paste0("Found ", length(vecDEGenes), " DE genes",
" at a FDR corrected p-value cut off of ", scaQThres,
".")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
}
else {
vecDEGenes <- NULL
}
objectImpulseDE2 <- set_vecDEGenes(obj = objectImpulseDE2,
element = vecDEGenes)
})
--- call from argument ---
if (class(matCountData) == "SummarizedExperiment") {
matCountData <- assay(matCountData)
}
--- R stacktrace ---
where 1: system.time({
strMessage <- "# Process input"
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
if (class(matCountData) == "SummarizedExperiment") {
matCountData <- assay(matCountData)
}
lsProcessedData <- processData(dfAnnotation = dfAnnotation,
matCountData = matCountData, boolCaseCtrl = boolCaseCtrl,
vecConfounders = vecConfounders, vecDispersionsExternal = vecDispersionsExternal,
vecSizeFactorsExternal = vecSizeFactorsExternal)
matCountDataProc <- lsProcessedData$matCountDataProc
dfAnnotationProc <- lsProcessedData$dfAnnotationProc
vecSizeFactorsExternalProc <- lsProcessedData$vecSizeFactorsExternalProc
vecDispersionsExternalProc <- lsProcessedData$vecDispersionsExternalProc
if (boolVerbose) {
write(lsProcessedData$strReportProcessing, file = "",
ncolumns = 1)
}
strReport <- paste0(strReport, lsProcessedData$strReportProcessing)
if (scaNProc > 1) {
register(MulticoreParam(workers = scaNProc))
}
else {
register(SerialParam())
}
if (is.null(vecDispersionsExternal)) {
strMessage <- paste0("# Run DESeq2: Using dispersion factors",
"computed by DESeq2.")
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
tm_runDESeq2 <- system.time({
vecDispersions <- runDESeq2(dfAnnotationProc = dfAnnotationProc,
matCountDataProc = matCountDataProc, boolCaseCtrl = boolCaseCtrl,
vecConfounders = vecConfounders)
})
strMessage <- paste0("Consumed time: ", round(tm_runDESeq2["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
}
else {
strMessage <- "# Using externally supplied dispersion factors."
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
vecDispersions <- vecDispersionsExternalProc
}
strMessage <- "# Compute size factors"
if (boolVerbose) {
message(strMessage)
}
strReport <- paste0(strReport, "\n", strMessage)
vecSizeFactors <- computeNormConst(matCountDataProc = matCountDataProc,
vecSizeFactorsExternal = vecSizeFactorsExternalProc)
objectImpulseDE2 <- new("ImpulseDE2Object", dfImpulseDE2Results = NULL,
vecDEGenes = NULL, lsModelFits = NULL, matCountDataProc = matCountDataProc,
vecAllIDs = rownames(matCountData), dfAnnotationProc = dfAnnotationProc,
vecSizeFactors = vecSizeFactors, vecDispersions = vecDispersions,
boolCaseCtrl = boolCaseCtrl, vecConfounders = vecConfounders,
scaNProc = scaNProc, scaQThres = scaQThres, strReport = strReport)
strMessage <- "# Fitting null and alternative model to the genes"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
tm_fitImpulse <- system.time({
objectImpulseDE2 <- fitModels(objectImpulseDE2 = objectImpulseDE2,
vecConfounders = vecConfounders, boolCaseCtrl = boolCaseCtrl)
})
strMessage <- paste0("Consumed time: ", round(tm_fitImpulse["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
if (boolIdentifyTransients) {
strMessage <- "# Fitting sigmoid model to case condition"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
tm_fitSigmoid <- system.time({
objectImpulseDE2 <- fitSigmoidModels(objectImpulseDE2 = objectImpulseDE2,
vecConfounders = vecConfounders, strCondition = "case")
})
strMessage <- paste0("Consumed time: ", round(tm_fitSigmoid["elapsed"]/60,
2), " min.")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
}
strMessage <- "# Differentially expression analysis based on model fits"
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
objectImpulseDE2 <- runDEAnalysis(objectImpulseDE2 = objectImpulseDE2,
boolCaseCtrl = get_boolCaseCtrl(obj = objectImpulseDE2),
boolIdentifyTransients = boolIdentifyTransients)
if (!is.null(scaQThres)) {
vecDEGenes <- as.vector(objectImpulseDE2$dfImpulseDE2Results[as.numeric(objectImpulseDE2$dfImpulseDE2Results$padj) <=
scaQThres, "Gene"])
strMessage <- paste0("Found ", length(vecDEGenes), " DE genes",
" at a FDR corrected p-value cut off of ", scaQThres,
".")
if (boolVerbose) {
message(strMessage)
}
objectImpulseDE2 <- append_strReport(obj = objectImpulseDE2,
s = strMessage)
}
else {
vecDEGenes <- NULL
}
objectImpulseDE2 <- set_vecDEGenes(obj = objectImpulseDE2,
element = vecDEGenes)
})
where 2: runImpulseDE2(matCountData = lsSimulatedData$matObservedCounts,
dfAnnotation = lsSimulatedData$dfAnnotation, boolCaseCtrl = FALSE,
vecConfounders = NULL, boolIdentifyTransients = FALSE, scaNProc = 1)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (expr, gcFirst = TRUE)
{
ppt <- function(y) {
if (!is.na(y[4L]))
y[1L] <- y[1L] + y[4L]
if (!is.na(y[5L]))
y[2L] <- y[2L] + y[5L]
paste(formatC(y[1L:3L]), collapse = " ")
}
if (gcFirst)
gc(FALSE)
time <- proc.time()
on.exit(message("Timing stopped at: ", ppt(proc.time() -
time)))
expr
new.time <- proc.time()
on.exit()
structure(new.time - time, class = "proc_time")
}
<bytecode: 0x000000002cfe1b60>
<environment: namespace:base>
--- function search by body ---
Function system.time in namespace base has this body.
----------- END OF FAILURE REPORT --------------
Fatal error: the condition has length > 1
* 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: 2 ERRORs, 1 WARNING, 1 NOTE
See
'C:/Users/biocbuild/bbs-3.12-bioc/meat/ImpulseDE2.Rcheck/00check.log'
for details.