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CHECK report for TCC on merida2

This page was generated on 2018-10-17 08:51:56 -0400 (Wed, 17 Oct 2018).

Package 1466/1561HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
TCC 1.20.1
Jianqiang Sun
Snapshot Date: 2018-10-15 16:45:08 -0400 (Mon, 15 Oct 2018)
URL: https://git.bioconductor.org/packages/TCC
Branch: RELEASE_3_7
Last Commit: 075b9fe
Last Changed Date: 2018-08-21 04:11:06 -0400 (Tue, 21 Aug 2018)
malbec2 Linux (Ubuntu 16.04.1 LTS) / x86_64  OK  OK  OK UNNEEDED, same version exists in internal repository
tokay2 Windows Server 2012 R2 Standard / x64  OK  OK  WARNINGS  OK UNNEEDED, same version exists in internal repository
merida2 OS X 10.11.6 El Capitan / x86_64  OK  OK [ OK ] OK UNNEEDED, same version exists in internal repository

Summary

Package: TCC
Version: 1.20.1
Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:TCC.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings TCC_1.20.1.tar.gz
StartedAt: 2018-10-17 00:22:54 -0400 (Wed, 17 Oct 2018)
EndedAt: 2018-10-17 00:35:57 -0400 (Wed, 17 Oct 2018)
EllapsedTime: 783.7 seconds
RetCode: 0
Status:  OK 
CheckDir: TCC.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:TCC.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings TCC_1.20.1.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.7-bioc/meat/TCC.Rcheck’
* using R version 3.5.1 Patched (2018-07-12 r74967)
* using platform: x86_64-apple-darwin15.6.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘TCC/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘TCC’ version ‘1.20.1’
* 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 ‘TCC’ 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 ... 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 contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU or elapsed time > 5s
                     user system elapsed
simulateReadCounts 27.874  0.092  28.297
calcAUCValue       20.349  0.114  20.649
plotFCPseudocolor  17.857  0.063  18.077
calcNormFactors    14.796  0.128  15.033
TCC-class          14.519  0.392  15.079
plot.TCC           12.194  0.172  12.495
hypoData_mg         8.673  0.025   8.791
hypoData            8.173  0.028   8.250
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.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: OK

Installation output

TCC.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD INSTALL TCC
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/3.5/Resources/library’
* installing *source* package ‘TCC’ ...
** R
** data
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘calcNormFactors’ in package ‘TCC’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
* DONE (TCC)

Tests output

TCC.Rcheck/tests/runTests.Rout


R version 3.5.1 Patched (2018-07-12 r74967) -- "Feather Spray"
Copyright (C) 2018 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.

> BiocGenerics:::testPackage("TCC")

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")'.

locfit 1.5-9.1 	 2013-03-22
    Welcome to 'DESeq'. For improved performance, usability and
    functionality, please consider migrating to 'DESeq2'.

Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid


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 objects are masked from 'package:base':

    aperm, apply


Attaching package: 'DESeq2'

The following objects are masked from 'package:DESeq':

    estimateSizeFactorsForMatrix, getVarianceStabilizedData,
    varianceStabilizingTransformation


Attaching package: 'limma'

The following object is masked from 'package:DESeq2':

    plotMA

The following object is masked from 'package:DESeq':

    plotMA

The following object is masked from 'package:BiocGenerics':

    plotMA


Attaching package: 'TCC'

The following object is masked from 'package:edgeR':

    calcNormFactors

TCC::INFO: Identifying DE genes using wad ...
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using wad ...
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using tmm ...
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 3 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 2 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 3 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 3 )
TCC::INFO: Done.
TCC::INFO: Generating simulation data under NB distribution ...
TCC::INFO: (genesizes   :  1000 )
TCC::INFO: (replicates  :  3, 3 )
TCC::INFO: (PDEG        :  0.16, 0.04 )
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ bayseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ bayseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ bayseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using bayseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.7357281
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8601875
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq2 - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq2 - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq2 - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq2 ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8598406
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ edger - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ edger - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using edger ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8734719
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ voom - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ voom - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ voom - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using voom ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8310656
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Generating simulation data under NB distribution ...
TCC::INFO: (genesizes   :  1000 )
TCC::INFO: (replicates  :  1, 1 )
TCC::INFO: (PDEG        :  0.16, 0.04 )
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ bayseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ bayseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ bayseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using bayseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.6686031
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: Warning messages:
1: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
2: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
3: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
4: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: Warning messages:
1: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
2: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: Warning messages:
1: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
2: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8193219
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq2 - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq2 - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq2 - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq2 ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8374125
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ edger - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ edger - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using edger ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8095375
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Generating simulation data under NB distribution ...
TCC::INFO: (genesizes   :  1000 )
TCC::INFO: (samples     :  8 )
TCC::INFO: (factors     :  2 )
TCC::INFO: (PDEG        :  0.1 )
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ bayseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ bayseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ bayseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using bayseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.6295278
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: Warning messages:
1: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
2: In checkForExperimentalReplicates(object, modelMatrix) : 

  Deprectation note: Analysis of designs without replicates will be removed
  in the Oct 2018 release: DESeq2 v1.22.0, after which DESeq2 will give an error.

3: In checkForExperimentalReplicates(object, modelMatrix) : 

  The design matrix has the same number of samples and coefficients to fit,
  estimating dispersion by treating samples as replicates. This analysis
  is not useful for accurate differential expression analysis, and arguably
  not for data exploration either, as large differences appear as high dispersion.

4: In checkForExperimentalReplicates(object, modelMatrix) : 

  Deprectation note: Analysis of designs without replicates will be removed
  in the Oct 2018 release: DESeq2 v1.22.0, after which DESeq2 will give an error.

5: In checkForExperimentalReplicates(object, modelMatrix) : 

  The design matrix has the same number of samples and coefficients to fit,
  estimating dispersion by treating samples as replicates. This analysis
  is not useful for accurate differential expression analysis, and arguably
  not for data exploration either, as large differences appear as high dispersion.

6: In checkForExperimentalReplicates(object, modelMatrix) : 

  Deprectation note: Analysis of designs without replicates will be removed
  in the Oct 2018 release: DESeq2 v1.22.0, after which DESeq2 will give an error.

7: In checkForExperimentalReplicates(object, modelMatrix) : 

  The design matrix has the same number of samples and coefficients to fit,
  estimating dispersion by treating samples as replicates. This analysis
  is not useful for accurate differential expression analysis, and arguably
  not for data exploration either, as large differences appear as high dispersion.

8: In checkForExperimentalReplicates(object, modelMatrix) : 

  Deprectation note: Analysis of designs without replicates will be removed
  in the Oct 2018 release: DESeq2 v1.22.0, after which DESeq2 will give an error.

9: In checkForExperimentalReplicates(object, modelMatrix) : 

  The design matrix has the same number of samples and coefficients to fit,
  estimating dispersion by treating samples as replicates. This analysis
  is not useful for accurate differential expression analysis, and arguably
  not for data exploration either, as large differences appear as high dispersion.

10: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: There were 43 warnings (use warnings() to see them)
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: There were 43 warnings (use warnings() to see them)
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8933889
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq2 - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq2 - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq2 - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq2 ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8666111
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ edger - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ edger - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using edger ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8878222
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ voom - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ voom - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ voom - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using voom ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8541889
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Generating simulation data under NB distribution ...
TCC::INFO: (genesizes   :  1000 )
TCC::INFO: (replicates  :  3, 3, 3 )
TCC::INFO: (PDEG        :  0.12, 0.04, 0.04 )
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ bayseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ bayseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ bayseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using bayseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.6940969
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.9056812
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq2 - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq2 - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq2 - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq2 ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.88775
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ edger - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ edger - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using edger ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.9158812
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ voom - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ voom - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ voom - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using voom ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8508562
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Generating simulation data under NB distribution ...
TCC::INFO: (genesizes   :  1000 )
TCC::INFO: (replicates  :  1, 1, 1 )
TCC::INFO: (PDEG        :  0.12, 0.04, 0.04 )
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ bayseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ bayseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ bayseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using bayseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.7288406
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: There were 50 or more warnings (use warnings() to see the first 50)
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: Warning messages:
1: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
2: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
Error in .local(object, ...) : 
  None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.
In addition: Warning messages:
1: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
2: In .local(object, ...) :
  in estimateDispersions: Ignoring extra argument(s).
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8036156
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq2 - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq2 - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq2 - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq2 ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.7980656
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ edger - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ edger - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using edger ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.7655781
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Generating simulation data under NB distribution ...
TCC::INFO: (genesizes   :  1000 )
TCC::INFO: (samples     :  12 )
TCC::INFO: (factors     :  2 )
TCC::INFO: (PDEG        :  0.1 )
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ bayseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ bayseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ bayseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using bayseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.6626682
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.9061809
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ deseq2 - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ deseq2 - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ deseq2 - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using deseq2 ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.9016178
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ edger - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ edger - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ edger - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using edger ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.9216906
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : tmm - [ voom - tmm ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq - [ voom - deseq ] X 1 )
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using DEGES
TCC::INFO: (iDEGES pipeline : deseq2 - [ voom - deseq2 ] X 1 )
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using voom ...
TCC::INFO: Done.
NA in cutpts forces recomputation using smallest gap
[1] 0.8510324
NA in cutpts forces recomputation using smallest gap
TCC::INFO: Calculating normalization factors using tmm ...
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using edger ...
TCC::INFO: Done.
TCC::INFO: Calculating normalization factors using tmm ...
TCC::INFO: Done.
TCC::INFO: Identifying DE genes using edger ...
TCC::INFO: Done.
TCC::INFO: Generating simulation data under NB distribution ...
TCC::INFO: (genesizes   :  1000 )
TCC::INFO: (replicates  :  3, 3 )
TCC::INFO: (PDEG        :  0.18, 0.02 )
TCC::INFO: Generating simulation data under NB distribution ...
TCC::INFO: (genesizes   :  1000 )
TCC::INFO: (replicates  :  3, 3, 3 )
TCC::INFO: (PDEG        :  0.18, 0.01, 0.01 )


RUNIT TEST PROTOCOL -- Wed Oct 17 00:35:50 2018 
*********************************************** 
Number of test functions: 10 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
TCC RUnit Tests - 10 test functions, 0 errors, 0 failures
Number of test functions: 10 
Number of errors: 0 
Number of failures: 0 
There were 50 or more warnings (use warnings() to see the first 50)
> 
> proc.time()
   user  system elapsed 
426.078   1.925 455.646

Example timings

TCC.Rcheck/TCC-Ex.timings

nameusersystemelapsed
ROKU0.0260.0050.033
TCC-class14.519 0.39215.079
TCC0.0150.0030.018
WAD0.2720.0100.283
arab0.0620.0050.144
calcAUCValue20.349 0.11420.649
calcNormFactors14.796 0.12815.033
clusterSample0.0700.0070.078
estimateDE1.4900.0241.530
filterLowCountGenes0.0360.0040.041
getNormalizedData0.3380.0050.347
getResult1.8820.0251.916
hypoData8.1730.0288.250
hypoData_mg8.6730.0258.791
hypoData_ts0.0020.0020.004
makeFCMatrix0.0030.0000.004
nakai0.0400.0030.044
plot.TCC12.194 0.17212.495
plotFCPseudocolor17.857 0.06318.077
simulateReadCounts27.874 0.09228.297