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###
### Running command:
###
### C:\Users\biocbuild\bbs-3.11-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:ImpulseDE.install-out.txt --library=C:\Users\biocbuild\bbs-3.11-bioc\R\library --no-vignettes --timings ImpulseDE_1.14.0.tar.gz
###
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* using log directory 'C:/Users/biocbuild/bbs-3.11-bioc/meat/ImpulseDE.Rcheck'
* using R version 4.0.3 (2020-10-10)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* using option '--no-vignettes'
* checking for file 'ImpulseDE/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'ImpulseDE' version '1.14.0'
* 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 'ImpulseDE' 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 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 ... OK
* 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 'ImpulseDE-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: impulse_DE
> ### Title: Differential expression analysis using impulse models
> ### Aliases: impulseDE impulse_DE
>
> ### ** Examples
>
> #' Install package longitudinal and load it
> library(longitudinal)
Loading required package: corpcor
> #' Attach datasets
> data(tcell)
> #' check dimension of data matrix of interest
> dim(tcell.10)
[1] 100 58
> #' generate a proper annotation table
> annot <- as.data.frame(cbind("Time" =
+ sort(rep(get.time.repeats(tcell.10)$time,10)),
+ "Condition" = "activated"), stringsAsFactors = FALSE)
> #' Time columns must be numeric
> annot$Time <- as.numeric(annot$Time)
> #' rownames of annotation table must appear in data table
> rownames(annot) = rownames(tcell.10)
> #' apply ImpulseDE in single time course mode
> #' since genes must be in rows, transpose data matrix using t()
> #' For the example, reduce iterations to 10, randomizations to 50, number of
> #' genes to 20 and number of used processors to 1:
> impulse_results <- impulse_DE(t(tcell.10)[1:20,], annot, "Time", "Condition",
+ n_iter = 10, n_randoms = 50, n_process = 1)
[1] "START: Prepare annotation table for internal usage"
[1] "-------------------------------------------------------------------"
[1] "Case condition: activated"
[1] "DONE"
[1] "###################################################################"
[1] "START: Clustering genes for Impulse model fit"
[1] "-------------------------------------------------------------------"
[1] "Clustering of case data set"
[1] "- 13 genes were excluded due to very low variation"
[1] "--- Number of correlation-based pre-clusters: 1"
[1] "------ Number of genes in pre-clusters: C1: 7"
[1] "--- Final number of clusters: 1"
[1] "------ Number of genes in final clusters: C1: 7"
[1] "DONE"
[1] "Consumed time: 0.03 min"
[1] "##################################################################"
[1] "START: Fitting Impulse model to the clusters"
[1] "-------------------------------------------------------------------"
[1] "DONE"
[1] "Consumed time: 0.02 min"
[1] "###################################################################"
[1] "START: Fitting Impulse model to the genes"
[1] "-------------------------------------------------------------------"
[1] "DONE"
[1] "Consumed time: 0.39 min"
[1] "###################################################################"
[1] "START: Generate background"
[1] "-------------------------------------------------------------------"
[1] "DONE"
[1] "Consumed time: 0.34 min"
[1] "###################################################################"
[1] "START: DE analysis"
[1] "-------------------------------------------------------------------"
----------- FAILURE REPORT --------------
--- failure: length > 1 in coercion to logical ---
--- srcref ---
:
--- package (from environment) ---
ImpulseDE
--- call from context ---
which(x > 2 || x < 0.5)
--- call from argument ---
x > 2 || x < 0.5
--- R stacktrace ---
where 1: which(x > 2 || x < 0.5)
where 2: FUN(newX[, i], ...)
where 3: apply(Ratios_TPs, 1, function(x) {
if (length(which(x > 2 || x < 0.5)) >= 2) {
"DE"
}
else {
"not_DE"
}
})
where 4: DE_analysis(expression_table, prepared_annotation, impulse_fit_genes,
background_results, control_timecourse, control_name, expr_type,
Q_value)
where 5: system.time({
impulse_DE_genes <- DE_analysis(expression_table, prepared_annotation,
impulse_fit_genes, background_results, control_timecourse,
control_name, expr_type, Q_value)
})
where 6: system.time({
print("START: Prepare annotation table for internal usage")
print("-------------------------------------------------------------------")
prepared_annotation <- annotation_preparation(annotation_table,
expression_table, colname_time, colname_condition, control_timecourse,
control_name, case_name)
prepared_annotation <- prepared_annotation[order(prepared_annotation$Condition),
]
prepared_annotation <- prepared_annotation[order(prepared_annotation$Time),
]
print("DONE")
print("###################################################################")
expression_table <- as.matrix(expression_table)
expression_table <- expression_table[, rownames(prepared_annotation)]
indx <- apply(expression_table, 1, function(x) {
TRUE %in% is.na(x)
})
expression_table <- expression_table[!(indx), ]
if (is.null(rownames(expression_table))) {
rownames(expression_table) <- paste("G", 1:nrow(expression_table),
sep = "_")
}
else if (length(grep("[a-zA-Z]", rownames(expression_table))) ==
0) {
rownames(expression_table) <- paste(rownames(expression_table),
"G", sep = "_")
}
print("START: Clustering genes for Impulse model fit")
print("-------------------------------------------------------------------")
tm_clust <- system.time({
clustering_results <- cluster_genes_for_impulse(expression_table,
prepared_annotation, control_timecourse, control_name,
plot_clusters, n_device = new_device)
})
print("DONE")
print(paste("Consumed time: ", round(tm_clust["elapsed"]/60,
2), " min", sep = ""))
print("##################################################################")
print("START: Fitting Impulse model to the clusters")
print("-------------------------------------------------------------------")
tm_imp_fit_clus <- system.time({
impulse_fit_clusters <- impulse_fit(clustering_results,
prepared_annotation, n_iter, control_timecourse,
control_name, n_proc = n_process)
})
print("DONE")
print(paste("Consumed time: ", round(tm_imp_fit_clus["elapsed"]/60,
2), " min", sep = ""))
print("###################################################################")
print("START: Fitting Impulse model to the genes")
print("-------------------------------------------------------------------")
tm_imp_fit_gen <- system.time({
impulse_fit_genes <- impulse_fit(expression_table, prepared_annotation,
n_iter, control_timecourse, control_name, clustering_results,
impulse_fit_clusters, n_proc = n_process)
})
print("DONE")
print(paste("Consumed time: ", round(tm_imp_fit_gen["elapsed"]/60,
2), " min", sep = ""))
print("###################################################################")
print("START: Generate background")
print("-------------------------------------------------------------------")
tm_bg <- system.time({
background_results <- generate_background(expression_table,
prepared_annotation, n_iter, impulse_fit_genes, control_timecourse,
control_name, clustering_results, n_randoms, n_process)
})
print("DONE")
print(paste("Consumed time: ", round(tm_bg["elapsed"]/60,
2), " min", sep = ""))
print("###################################################################")
print("START: DE analysis")
print("-------------------------------------------------------------------")
tm_DE <- system.time({
impulse_DE_genes <- DE_analysis(expression_table, prepared_annotation,
impulse_fit_genes, background_results, control_timecourse,
control_name, expr_type, Q_value)
})
print("DONE")
print(paste("Consumed time: ", round(tm_DE["elapsed"]/60,
2), " min", sep = ""))
print("##################################################################")
})
where 7: impulse_DE(t(tcell.10)[1:20, ], annot, "Time", "Condition", n_iter = 10,
n_randoms = 50, n_process = 1)
--- value of length: 9 type: logical ---
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
--- function from context ---
function (x, arr.ind = FALSE, useNames = TRUE)
{
wh <- .Internal(which(x))
if (arr.ind && !is.null(d <- dim(x)))
arrayInd(wh, d, dimnames(x), useNames = useNames)
else wh
}
<bytecode: 0x01ff5438>
<environment: namespace:base>
--- function search by body ---
Function which in namespace base has this body.
----------- END OF FAILURE REPORT --------------
Fatal error: length > 1 in coercion to logical
** running examples for arch 'x64' ... ERROR
Running examples in 'ImpulseDE-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: impulse_DE
> ### Title: Differential expression analysis using impulse models
> ### Aliases: impulseDE impulse_DE
>
> ### ** Examples
>
> #' Install package longitudinal and load it
> library(longitudinal)
Loading required package: corpcor
> #' Attach datasets
> data(tcell)
> #' check dimension of data matrix of interest
> dim(tcell.10)
[1] 100 58
> #' generate a proper annotation table
> annot <- as.data.frame(cbind("Time" =
+ sort(rep(get.time.repeats(tcell.10)$time,10)),
+ "Condition" = "activated"), stringsAsFactors = FALSE)
> #' Time columns must be numeric
> annot$Time <- as.numeric(annot$Time)
> #' rownames of annotation table must appear in data table
> rownames(annot) = rownames(tcell.10)
> #' apply ImpulseDE in single time course mode
> #' since genes must be in rows, transpose data matrix using t()
> #' For the example, reduce iterations to 10, randomizations to 50, number of
> #' genes to 20 and number of used processors to 1:
> impulse_results <- impulse_DE(t(tcell.10)[1:20,], annot, "Time", "Condition",
+ n_iter = 10, n_randoms = 50, n_process = 1)
[1] "START: Prepare annotation table for internal usage"
[1] "-------------------------------------------------------------------"
[1] "Case condition: activated"
[1] "DONE"
[1] "###################################################################"
[1] "START: Clustering genes for Impulse model fit"
[1] "-------------------------------------------------------------------"
[1] "Clustering of case data set"
[1] "- 13 genes were excluded due to very low variation"
[1] "--- Number of correlation-based pre-clusters: 1"
[1] "------ Number of genes in pre-clusters: C1: 7"
[1] "--- Final number of clusters: 1"
[1] "------ Number of genes in final clusters: C1: 7"
[1] "DONE"
[1] "Consumed time: 0.01 min"
[1] "##################################################################"
[1] "START: Fitting Impulse model to the clusters"
[1] "-------------------------------------------------------------------"
[1] "DONE"
[1] "Consumed time: 0.02 min"
[1] "###################################################################"
[1] "START: Fitting Impulse model to the genes"
[1] "-------------------------------------------------------------------"
[1] "DONE"
[1] "Consumed time: 0.39 min"
[1] "###################################################################"
[1] "START: Generate background"
[1] "-------------------------------------------------------------------"
[1] "DONE"
[1] "Consumed time: 0.36 min"
[1] "###################################################################"
[1] "START: DE analysis"
[1] "-------------------------------------------------------------------"
----------- FAILURE REPORT --------------
--- failure: length > 1 in coercion to logical ---
--- srcref ---
:
--- package (from environment) ---
ImpulseDE
--- call from context ---
which(x > 2 || x < 0.5)
--- call from argument ---
x > 2 || x < 0.5
--- R stacktrace ---
where 1: which(x > 2 || x < 0.5)
where 2: FUN(newX[, i], ...)
where 3: apply(Ratios_TPs, 1, function(x) {
if (length(which(x > 2 || x < 0.5)) >= 2) {
"DE"
}
else {
"not_DE"
}
})
where 4: DE_analysis(expression_table, prepared_annotation, impulse_fit_genes,
background_results, control_timecourse, control_name, expr_type,
Q_value)
where 5: system.time({
impulse_DE_genes <- DE_analysis(expression_table, prepared_annotation,
impulse_fit_genes, background_results, control_timecourse,
control_name, expr_type, Q_value)
})
where 6: system.time({
print("START: Prepare annotation table for internal usage")
print("-------------------------------------------------------------------")
prepared_annotation <- annotation_preparation(annotation_table,
expression_table, colname_time, colname_condition, control_timecourse,
control_name, case_name)
prepared_annotation <- prepared_annotation[order(prepared_annotation$Condition),
]
prepared_annotation <- prepared_annotation[order(prepared_annotation$Time),
]
print("DONE")
print("###################################################################")
expression_table <- as.matrix(expression_table)
expression_table <- expression_table[, rownames(prepared_annotation)]
indx <- apply(expression_table, 1, function(x) {
TRUE %in% is.na(x)
})
expression_table <- expression_table[!(indx), ]
if (is.null(rownames(expression_table))) {
rownames(expression_table) <- paste("G", 1:nrow(expression_table),
sep = "_")
}
else if (length(grep("[a-zA-Z]", rownames(expression_table))) ==
0) {
rownames(expression_table) <- paste(rownames(expression_table),
"G", sep = "_")
}
print("START: Clustering genes for Impulse model fit")
print("-------------------------------------------------------------------")
tm_clust <- system.time({
clustering_results <- cluster_genes_for_impulse(expression_table,
prepared_annotation, control_timecourse, control_name,
plot_clusters, n_device = new_device)
})
print("DONE")
print(paste("Consumed time: ", round(tm_clust["elapsed"]/60,
2), " min", sep = ""))
print("##################################################################")
print("START: Fitting Impulse model to the clusters")
print("-------------------------------------------------------------------")
tm_imp_fit_clus <- system.time({
impulse_fit_clusters <- impulse_fit(clustering_results,
prepared_annotation, n_iter, control_timecourse,
control_name, n_proc = n_process)
})
print("DONE")
print(paste("Consumed time: ", round(tm_imp_fit_clus["elapsed"]/60,
2), " min", sep = ""))
print("###################################################################")
print("START: Fitting Impulse model to the genes")
print("-------------------------------------------------------------------")
tm_imp_fit_gen <- system.time({
impulse_fit_genes <- impulse_fit(expression_table, prepared_annotation,
n_iter, control_timecourse, control_name, clustering_results,
impulse_fit_clusters, n_proc = n_process)
})
print("DONE")
print(paste("Consumed time: ", round(tm_imp_fit_gen["elapsed"]/60,
2), " min", sep = ""))
print("###################################################################")
print("START: Generate background")
print("-------------------------------------------------------------------")
tm_bg <- system.time({
background_results <- generate_background(expression_table,
prepared_annotation, n_iter, impulse_fit_genes, control_timecourse,
control_name, clustering_results, n_randoms, n_process)
})
print("DONE")
print(paste("Consumed time: ", round(tm_bg["elapsed"]/60,
2), " min", sep = ""))
print("###################################################################")
print("START: DE analysis")
print("-------------------------------------------------------------------")
tm_DE <- system.time({
impulse_DE_genes <- DE_analysis(expression_table, prepared_annotation,
impulse_fit_genes, background_results, control_timecourse,
control_name, expr_type, Q_value)
})
print("DONE")
print(paste("Consumed time: ", round(tm_DE["elapsed"]/60,
2), " min", sep = ""))
print("##################################################################")
})
where 7: impulse_DE(t(tcell.10)[1:20, ], annot, "Time", "Condition", n_iter = 10,
n_randoms = 50, n_process = 1)
--- value of length: 9 type: logical ---
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
--- function from context ---
function (x, arr.ind = FALSE, useNames = TRUE)
{
wh <- .Internal(which(x))
if (arr.ind && !is.null(d <- dim(x)))
arrayInd(wh, d, dimnames(x), useNames = useNames)
else wh
}
<bytecode: 0x00000000051beac8>
<environment: namespace:base>
--- function search by body ---
Function which in namespace base has this body.
----------- END OF FAILURE REPORT --------------
Fatal error: length > 1 in coercion to logical
* 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
See
'C:/Users/biocbuild/bbs-3.11-bioc/meat/ImpulseDE.Rcheck/00check.log'
for details.