Davide Risso
| Snapshot Date: 2019-04-15 17:01:12 -0400 (Mon, 15 Apr 2019) |
| URL: https://git.bioconductor.org/packages/RUVSeq |
| Branch: RELEASE_3_8 |
| Last Commit: 2edc83a |
| Last Changed Date: 2019-01-04 13:47:46 -0400 (Fri, 04 Jan 2019) |
| Back to Multiple platform build/check report for BioC 3.8 |
|
This page was generated on 2019-04-16 11:57:43 -0400 (Tue, 16 Apr 2019).
| Package 1373/1649 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||
| RUVSeq 1.16.1 Davide Risso
| malbec1 | Linux (Ubuntu 16.04.6 LTS) / x86_64 | OK | OK | OK | | ||||||
| merida1 | OS X 10.11.6 El Capitan / x86_64 | OK | OK | [ OK ] | OK | |
| Package: RUVSeq |
| Version: 1.16.1 |
| Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:RUVSeq.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings RUVSeq_1.16.1.tar.gz |
| StartedAt: 2019-04-16 02:34:42 -0400 (Tue, 16 Apr 2019) |
| EndedAt: 2019-04-16 02:39:40 -0400 (Tue, 16 Apr 2019) |
| EllapsedTime: 297.9 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: RUVSeq.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:RUVSeq.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings RUVSeq_1.16.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/Users/biocbuild/bbs-3.8-bioc/meat/RUVSeq.Rcheck’
* using R version 3.5.3 (2019-03-11)
* using platform: x86_64-apple-darwin15.6.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘RUVSeq/DESCRIPTION’ ... OK
* this is package ‘RUVSeq’ version ‘1.16.1’
* 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 ‘RUVSeq’ 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
* 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
residuals.DGEGLM : <anonymous>: no visible global function definition
for ‘poisson’
Undefined global functions or variables:
poisson
Consider adding
importFrom("stats", "poisson")
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 sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘RUVg.R’
Running ‘RUVr.R’
Running ‘RUVs.R’
OK
* 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 NOTE
See
‘/Users/biocbuild/bbs-3.8-bioc/meat/RUVSeq.Rcheck/00check.log’
for details.
RUVSeq.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD INSTALL RUVSeq ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/3.5/Resources/library’ * installing *source* package ‘RUVSeq’ ... ** R ** 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 * DONE (RUVSeq)
RUVSeq.Rcheck/tests/RUVg.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)
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(RUVSeq)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
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, append,
as.data.frame, basename, cbind, colMeans, colSums, colnames,
dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
intersect, is.unsorted, lapply, lengths, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: EDASeq
Loading required package: ShortRead
Loading required package: BiocParallel
Loading required package: Biostrings
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: IRanges
Loading required package: XVector
Attaching package: 'Biostrings'
The following object is masked from 'package:base':
strsplit
Loading required package: Rsamtools
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: GenomicAlignments
Loading required package: SummarizedExperiment
Loading required package: DelayedArray
Loading required package: matrixStats
Attaching package: 'matrixStats'
The following objects are masked from 'package:Biobase':
anyMissing, rowMedians
Attaching package: 'DelayedArray'
The following objects are masked from 'package:matrixStats':
colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges
The following object is masked from 'package:Biostrings':
type
The following objects are masked from 'package:base':
aperm, apply
Loading required package: edgeR
Loading required package: limma
Attaching package: 'limma'
The following object is masked from 'package:BiocGenerics':
plotMA
>
> mat <- matrix(data=rpois(100, lambda=10), ncol=10)
> rownames(mat) <- paste("gene", 1:10, sep="")
>
> es <- newSeqExpressionSet(mat)
>
> ## dimension of W
> ks <- 1:5
>
> ## matrix
> r1 <- lapply(ks, function(k) RUVg(mat, 1:10, k))
>
> print(sapply(r1, function(x) dim(x$W)))
[,1] [,2] [,3] [,4] [,5]
[1,] 10 10 10 10 10
[2,] 1 2 3 4 5
> stopifnot(all(lapply(r1, function(x) dim(x$W)[2])==ks))
>
> ## already logged data
> r1b <- lapply(ks, function(k) RUVg(log(mat+1), 1:10, k))
Warning messages:
1: In RUVg(log(mat + 1), 1:10, k) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
2: In RUVg(log(mat + 1), 1:10, k) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
3: In RUVg(log(mat + 1), 1:10, k) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
4: In RUVg(log(mat + 1), 1:10, k) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
5: In RUVg(log(mat + 1), 1:10, k) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
> r1c <- lapply(ks, function(k) RUVg(log(mat+1), 1:10, k, isLog=TRUE))
> r1d <- lapply(ks, function(k) RUVg(mat, 1:10, k, round=FALSE))
>
> stopifnot(all(sapply(ks, function(i) all(r1[[i]]$W==r1c[[i]]$W))))
> stopifnot(all(sapply(ks, function(i) all(r1d[[i]]$W==r1c[[i]]$W))))
>
> stopifnot(all(sapply(ks, function(i) all(log(r1d[[i]]$normalizedCounts+1)-r1c[[i]]$normalizedCounts<1e-8))))
>
> ## SeqExpressionSet
> r2 <- lapply(ks, function(k) RUVg(es, rownames(es)[1:10], k))
>
> print(sapply(r2, function(x) dim(pData(x))))
[,1] [,2] [,3] [,4] [,5]
[1,] 10 10 10 10 10
[2,] 1 2 3 4 5
> stopifnot(all(lapply(r2, function(x) dim(pData(x))[2])==ks))
>
> ## check handling of zeros
> mat <- matrix(data=rpois(100, lambda=2), ncol=10)
> rownames(mat) <- paste("gene", 1:10, sep="")
> r3 <- RUVg(mat, 1:10, k=1)
> print(table(mat==0))
FALSE TRUE
91 9
> print(table(r3$normalizedCounts==0))
FALSE TRUE
94 6
>
> proc.time()
user system elapsed
13.547 0.670 14.382
RUVSeq.Rcheck/tests/RUVr.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)
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(RUVSeq)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
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, append,
as.data.frame, basename, cbind, colMeans, colSums, colnames,
dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
intersect, is.unsorted, lapply, lengths, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: EDASeq
Loading required package: ShortRead
Loading required package: BiocParallel
Loading required package: Biostrings
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: IRanges
Loading required package: XVector
Attaching package: 'Biostrings'
The following object is masked from 'package:base':
strsplit
Loading required package: Rsamtools
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: GenomicAlignments
Loading required package: SummarizedExperiment
Loading required package: DelayedArray
Loading required package: matrixStats
Attaching package: 'matrixStats'
The following objects are masked from 'package:Biobase':
anyMissing, rowMedians
Attaching package: 'DelayedArray'
The following objects are masked from 'package:matrixStats':
colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges
The following object is masked from 'package:Biostrings':
type
The following objects are masked from 'package:base':
aperm, apply
Loading required package: edgeR
Loading required package: limma
Attaching package: 'limma'
The following object is masked from 'package:BiocGenerics':
plotMA
> library(edgeR)
>
> mat <- matrix(data=rpois(100, lambda=10), ncol=10)
> rownames(mat) <- paste("gene", 1:10, sep="")
>
> es <- newSeqExpressionSet(mat)
>
> ## compute edgeR residuals
> x <- as.factor(rep(c("Ctl", "Trt"), each=5))
> design <- model.matrix(˜x)
> y <- DGEList(counts=mat, group=x)
> y <- calcNormFactors(y, method="upperquartile")
> y <- estimateGLMCommonDisp(y, design)
> y <- estimateGLMTagwiseDisp(y, design)
>
> fit <- glmFit(y, design)
> res <- residuals(fit, type="deviance")
>
> ## dimension of W
> ks <- 1:5
>
> ## matrix
> r1 <- lapply(ks, function(k) RUVr(mat, 1:10, k, res))
>
> print(sapply(r1, function(x) dim(x$W)))
[,1] [,2] [,3] [,4] [,5]
[1,] 10 10 10 10 10
[2,] 1 2 3 4 5
> stopifnot(all(lapply(r1, function(x) dim(x$W)[2])==ks))
>
> ## already logged data
> r1b <- lapply(ks, function(k) RUVr(log(mat+1), 1:10, k, res))
Warning messages:
1: In RUVr(log(mat + 1), 1:10, k, res) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
2: In RUVr(log(mat + 1), 1:10, k, res) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
3: In RUVr(log(mat + 1), 1:10, k, res) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
4: In RUVr(log(mat + 1), 1:10, k, res) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
5: In RUVr(log(mat + 1), 1:10, k, res) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
> r1c <- lapply(ks, function(k) RUVr(log(mat+1), 1:10, k, res, isLog=TRUE))
> r1d <- lapply(ks, function(k) RUVr(mat, 1:10, k, res, round=FALSE))
>
> stopifnot(all(sapply(ks, function(i) all(r1[[i]]$W==r1c[[i]]$W))))
> stopifnot(all(sapply(ks, function(i) all(r1d[[i]]$W==r1c[[i]]$W))))
>
> stopifnot(all(sapply(ks, function(i) all(log(r1d[[i]]$normalizedCounts+1)-r1c[[i]]$normalizedCounts<1e-8))))
>
> ## SeqExpressionSet
> r2 <- lapply(ks, function(k) RUVr(es, rownames(es)[1:10], k, res))
>
> print(sapply(r2, function(x) dim(pData(x))))
[,1] [,2] [,3] [,4] [,5]
[1,] 10 10 10 10 10
[2,] 1 2 3 4 5
> stopifnot(all(lapply(r2, function(x) dim(pData(x))[2])==ks))
>
> ## check handling of zeros
> mat <- matrix(data=rpois(100, lambda=2), ncol=10)
> rownames(mat) <- paste("gene", 1:10, sep="")
> r3 <- RUVr(mat, 1:10, k=1, res)
> print(table(mat==0))
FALSE TRUE
88 12
> print(table(r3$normalizedCounts==0))
FALSE TRUE
90 10
>
> proc.time()
user system elapsed
14.341 0.674 15.146
RUVSeq.Rcheck/tests/RUVs.Rout
R version 3.5.3 (2019-03-11) -- "Great Truth"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)
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(RUVSeq)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
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, append,
as.data.frame, basename, cbind, colMeans, colSums, colnames,
dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
intersect, is.unsorted, lapply, lengths, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which, which.max, which.min
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: EDASeq
Loading required package: ShortRead
Loading required package: BiocParallel
Loading required package: Biostrings
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
expand.grid
Loading required package: IRanges
Loading required package: XVector
Attaching package: 'Biostrings'
The following object is masked from 'package:base':
strsplit
Loading required package: Rsamtools
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: GenomicAlignments
Loading required package: SummarizedExperiment
Loading required package: DelayedArray
Loading required package: matrixStats
Attaching package: 'matrixStats'
The following objects are masked from 'package:Biobase':
anyMissing, rowMedians
Attaching package: 'DelayedArray'
The following objects are masked from 'package:matrixStats':
colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges
The following object is masked from 'package:Biostrings':
type
The following objects are masked from 'package:base':
aperm, apply
Loading required package: edgeR
Loading required package: limma
Attaching package: 'limma'
The following object is masked from 'package:BiocGenerics':
plotMA
>
> mat <- matrix(data=rpois(100, lambda=10), ncol=10)
> rownames(mat) <- paste("gene", 1:10, sep="")
>
> differences <- matrix(data=c(1:3, 4:6), byrow=TRUE, nrow=2)
>
> es <- newSeqExpressionSet(mat)
>
> ## dimension of W
> ks <- 1:4
>
> ## matrix
> r1 <- lapply(ks, function(k) RUVs(mat, 1:10, k, differences))
>
> print(sapply(r1, function(x) dim(x$W)))
[,1] [,2] [,3] [,4]
[1,] 10 10 10 10
[2,] 1 2 3 4
> stopifnot(all(lapply(r1, function(x) dim(x$W)[2])==ks))
>
> ## already logged data
> r1b <- lapply(ks, function(k) RUVs(log(mat+1), 1:10, k, differences))
Warning messages:
1: In RUVs(log(mat + 1), 1:10, k, differences) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
2: In RUVs(log(mat + 1), 1:10, k, differences) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
3: In RUVs(log(mat + 1), 1:10, k, differences) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
4: In RUVs(log(mat + 1), 1:10, k, differences) :
The expression matrix does not contain counts.
Please, pass a matrix of counts (not logged) or set isLog to TRUE to skip the log transformation
> r1c <- lapply(ks, function(k) RUVs(log(mat+1), 1:10, k, differences, isLog=TRUE))
> r1d <- lapply(ks, function(k) RUVs(mat, 1:10, k, differences, round=FALSE))
>
> stopifnot(all(sapply(ks, function(i) all(r1[[i]]$W==r1c[[i]]$W))))
> stopifnot(all(sapply(ks, function(i) all(r1d[[i]]$W==r1c[[i]]$W))))
>
> stopifnot(all(sapply(ks, function(i) all(log(r1d[[i]]$normalizedCounts+1)-r1c[[i]]$normalizedCounts<1e-8))))
>
> ## SeqExpressionSet
> r2 <- lapply(ks, function(k) RUVs(es, rownames(es)[1:10], k, differences))
>
> print(sapply(r2, function(x) dim(pData(x))))
[,1] [,2] [,3] [,4]
[1,] 10 10 10 10
[2,] 1 2 3 4
> stopifnot(all(lapply(r2, function(x) dim(pData(x))[2])==ks))
>
> ## check handling of zeros
> mat <- matrix(data=rpois(100, lambda=2), ncol=10)
> rownames(mat) <- paste("gene", 1:10, sep="")
> r3 <- RUVs(mat, 1:10, k=1, differences)
> print(table(mat==0))
FALSE TRUE
85 15
> print(table(r3$normalizedCounts==0))
FALSE TRUE
87 13
>
> ## make groups
> factor1 <- rep(c("a", "b", "c"), each=3)
> factor2 <- c(rep("a", 4), rep("b", 2), rep("c", 3))
> factor3 <- rep(1:6, each=2)
>
> makeGroups(factor1)
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6
[3,] 7 8 9
> makeGroups(as.factor(factor1))
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6
[3,] 7 8 9
> makeGroups(factor2)
[,1] [,2] [,3] [,4]
[1,] 1 2 3 4
[2,] 5 6 -1 -1
[3,] 7 8 9 -1
> makeGroups(as.factor(factor2))
[,1] [,2] [,3] [,4]
[1,] 1 2 3 4
[2,] 5 6 -1 -1
[3,] 7 8 9 -1
> makeGroups(factor3)
[,1] [,2]
[1,] 1 2
[2,] 3 4
[3,] 5 6
[4,] 7 8
[5,] 9 10
[6,] 11 12
> makeGroups(as.factor(factor3))
[,1] [,2]
[1,] 1 2
[2,] 3 4
[3,] 5 6
[4,] 7 8
[5,] 9 10
[6,] 11 12
>
>
>
> proc.time()
user system elapsed
14.480 0.729 15.386
RUVSeq.Rcheck/RUVSeq-Ex.timings
| name | user | system | elapsed | |
| RUVg | 0.901 | 0.026 | 0.934 | |
| RUVr | 1.774 | 0.085 | 1.876 | |
| RUVs | 0.173 | 0.017 | 0.191 | |
| makeGroups | 0.001 | 0.000 | 0.001 | |
| residuals.DGEGLM | 0.829 | 0.019 | 0.858 | |