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BioC 3.2: CHECK report for MLSeq on oaxaca

This page was generated on 2015-08-24 10:58:16 -0700 (Mon, 24 Aug 2015).

Package 638/1071HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
MLSeq 1.7.0
Gokmen Zararsiz
Snapshot Date: 2015-08-23 16:24:14 -0700 (Sun, 23 Aug 2015)
URL: https://hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/MLSeq
Last Changed Rev: 102594 / Revision: 107696
Last Changed Date: 2015-04-16 13:02:44 -0700 (Thu, 16 Apr 2015)
zin1 Linux (Ubuntu 14.04.2 LTS) / x86_64  NotNeeded  OK  OK UNNEEDED, same version exists in internal repository
perceval Mac OS X Snow Leopard (10.6.8) / x86_64  NotNeeded  OK  OK  OK UNNEEDED, same version exists in internal repository
oaxaca Mac OS X Mavericks (10.9.5) / x86_64  NotNeeded  OK [ OK ] OK UNNEEDED, same version exists in internal repository

Summary

Package: MLSeq
Version: 1.7.0
Command: /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --no-vignettes --timings MLSeq_1.7.0.tar.gz
StartedAt: 2015-08-24 01:51:27 -0700 (Mon, 24 Aug 2015)
EndedAt: 2015-08-24 01:56:43 -0700 (Mon, 24 Aug 2015)
EllapsedTime: 316.0 seconds
RetCode: 0
Status:  OK 
CheckDir: MLSeq.Rcheck
Warnings: 0

Command output

##############################################################################
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###
### Running command:
###
###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --no-vignettes --timings MLSeq_1.7.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.2-bioc/meat/MLSeq.Rcheck’
* using R version 3.2.2 (2015-08-14)
* using platform: x86_64-apple-darwin13.4.0 (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘MLSeq/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘MLSeq’ version ‘1.7.0’
* checking package namespace information ... OK
* checking package dependencies ... NOTE
Depends: includes the non-default packages:
  ‘caret’ ‘DESeq2’ ‘Biobase’ ‘limma’ ‘randomForest’ ‘edgeR’
Adding so many packages to the search path is excessive and importing
selectively is preferable.
* 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 ‘MLSeq’ can be installed ... [24s/25s] 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 loading without being on the library search path ... 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
classify: no visible global function definition for
  ‘AnnotatedDataFrame’
classify: no visible global function definition for ‘bagControl’
classify: no visible binding for global variable ‘svmBag’
predictClassify: no visible global function definition for
  ‘AnnotatedDataFrame’
* 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 installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... [77s/78s] OK
Examples with CPU or elapsed time > 5s
                  user system elapsed
predictClassify 15.124  0.100  15.310
classify        14.948  0.136  15.169
confusionMat     5.938  0.055   6.024
normalization    5.875  0.034   5.955
deseqTransform   5.796  0.037   5.866
method           5.786  0.034   5.863
ref              5.688  0.028   5.760
trained          5.396  0.030   5.447
* 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 NOTEs
See
  ‘/Users/biocbuild/bbs-3.2-bioc/meat/MLSeq.Rcheck/00check.log’
for details.


MLSeq.Rcheck/00install.out:

* installing *source* package ‘MLSeq’ ...
** R
** data
** inst
** preparing package for lazy loading
Note: the specification for S3 class “family” in package ‘MatrixModels’ seems equivalent to one from package ‘lme4’: not turning on duplicate class definitions for this class.
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
Note: the specification for S3 class “family” in package ‘MatrixModels’ seems equivalent to one from package ‘lme4’: not turning on duplicate class definitions for this class.
* DONE (MLSeq)

MLSeq.Rcheck/MLSeq-Ex.timings:

nameusersystemelapsed
MLSeq-class0.0010.0000.000
cervical0.0060.0010.007
classify14.948 0.13615.169
confusionMat5.9380.0556.024
deseqTransform5.7960.0375.866
method5.7860.0345.863
normalization5.8750.0345.955
predictClassify15.124 0.10015.310
ref5.6880.0285.760
trained5.3960.0305.447