Back to Multiple platform build/check report for BioC 3.13
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This page was generated on 2021-10-15 15:05:40 -0400 (Fri, 15 Oct 2021).

CHECK results for evaluomeR on nebbiolo1

To the developers/maintainers of the evaluomeR package:
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raw results

Package 599/2041HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
evaluomeR 1.8.0  (landing page)
José Antonio Bernabé-Díaz
Snapshot Date: 2021-10-14 04:50:12 -0400 (Thu, 14 Oct 2021)
git_url: https://git.bioconductor.org/packages/evaluomeR
git_branch: RELEASE_3_13
git_last_commit: b88f5c0
git_last_commit_date: 2021-05-19 12:42:13 -0400 (Wed, 19 May 2021)
nebbiolo1Linux (Ubuntu 20.04.2 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
tokay2Windows Server 2012 R2 Standard / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
machv2macOS 10.14.6 Mojave / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published

Summary

Package: evaluomeR
Version: 1.8.0
Command: /home/biocbuild/bbs-3.13-bioc/R/bin/R CMD check --install=check:evaluomeR.install-out.txt --library=/home/biocbuild/bbs-3.13-bioc/R/library --no-vignettes --timings evaluomeR_1.8.0.tar.gz
StartedAt: 2021-10-14 09:46:33 -0400 (Thu, 14 Oct 2021)
EndedAt: 2021-10-14 09:49:57 -0400 (Thu, 14 Oct 2021)
EllapsedTime: 203.9 seconds
RetCode: 0
Status:   OK  
CheckDir: evaluomeR.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.13-bioc/R/bin/R CMD check --install=check:evaluomeR.install-out.txt --library=/home/biocbuild/bbs-3.13-bioc/R/library --no-vignettes --timings evaluomeR_1.8.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.13-bioc/meat/evaluomeR.Rcheck’
* using R version 4.1.1 (2021-08-10)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘evaluomeR/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘evaluomeR’ version ‘1.8.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... NOTE
Depends: includes the non-default packages:
  'SummarizedExperiment', 'MultiAssayExperiment', 'cluster', 'fpc',
  'randomForest', 'flexmix'
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 ‘evaluomeR’ 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 ... NOTE
File
  LICENSE
is not mentioned in the DESCRIPTION file.
* 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 ... NOTE
Namespace in Imports field not imported from: ‘kableExtra’
  All declared Imports should be used.
Packages in Depends field not imported from:
  ‘flexmix’ ‘randomForest’
  These packages need to be imported from (in the NAMESPACE file)
  for when this namespace is loaded but not attached.
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
flemixModel: no visible global function definition for ‘FLXMRglm’
flemixModel: no visible global function definition for ‘stepFlexmix’
flemixModel: no visible global function definition for ‘getModel’
globalMetric: no visible global function definition for ‘prior’
metrics_pca: no visible global function definition for ‘prcomp’
metrics_randomforest: no visible global function definition for
  ‘randomForest’
metrics_randomforest: no visible global function definition for ‘head’
speccCBI: no visible global function definition for ‘specc’
Undefined global functions or variables:
  FLXMRglm getModel head prcomp prior randomForest specc stepFlexmix
Consider adding
  importFrom("stats", "prcomp")
  importFrom("utils", "head")
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 contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking LazyData ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testAll.R’
  Running ‘testAnalysis.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: 4 NOTEs
See
  ‘/home/biocbuild/bbs-3.13-bioc/meat/evaluomeR.Rcheck/00check.log’
for details.



Installation output

evaluomeR.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.13-bioc/R/bin/R CMD INSTALL evaluomeR
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.13-bioc/R/library’
* installing *source* package ‘evaluomeR’ ...
** using staged installation
** R
** data
*** moving datasets to lazyload DB
** inst
** byte-compile and prepare package for lazy loading
** help
Loading required namespace: evaluomeR
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (evaluomeR)

Tests output

evaluomeR.Rcheck/tests/testAll.Rout


R version 4.1.1 (2021-08-10) -- "Kick Things"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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(evaluomeR)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

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

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: GenomicRanges
Loading required package: stats4
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, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

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

    rowMedians

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

    anyMissing, rowMedians

Loading required package: MultiAssayExperiment
Loading required package: cluster
Loading required package: fpc
Loading required package: randomForest
randomForest 4.6-14
Type rfNews() to see new features/changes/bug fixes.

Attaching package: 'randomForest'

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

    combine

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

    combine

Loading required package: flexmix
Loading required package: lattice
> 
> data("rnaMetrics")
> 
> dataFrame <- stability(data=rnaMetrics, k=4, bs=100, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 4
Processing metric: DegFact(2)
	Calculation of k = 4
> dataFrame <- stabilityRange(data=rnaMetrics, k.range=c(2,4), bs=20, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
Processing metric: DegFact(2)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
> assay(dataFrame)
     Metric    Mean_stability_k_2  Mean_stability_k_3  Mean_stability_k_4 
[1,] "RIN"     "0.825833333333333" "0.778412698412698" "0.69625"          
[2,] "DegFact" "0.955595238095238" "0.977777777777778" "0.820833333333333"
> # Metric    Mean_stability_k_2  Mean_stability_k_3  Mean_stability_k_4
> # [1,] "RIN"     "0.825833333333333" "0.778412698412698" "0.69625"
> # [2,] "DegFact" "0.955595238095238" "0.977777777777778" "0.820833333333333"
> dataFrame <- stabilitySet(data=rnaMetrics, k.set=c(2,3,4), bs=20, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
Processing metric: DegFact(2)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
> 
> dataFrame <- quality(data=rnaMetrics, cbi="kmeans", k=3, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 3
Processing metric: DegFact(2)
	Calculation of k = 3
> assay(dataFrame)
     Metric    Cluster_1_SilScore  Cluster_2_SilScore  Cluster_3_SilScore 
[1,] "RIN"     "0.420502645502646" "0.724044583696066" "0.68338517747747" 
[2,] "DegFact" "0.876516605981734" "0.643613928123002" "0.521618857725795"
     Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size
[1,] "0.627829396038413"  "4"            "4"            "8"           
[2,] "0.737191191352892"  "8"            "5"            "3"           
> # Metric    Cluster_1_SilScore  Cluster_2_SilScore  Cluster_3_SilScore
> # [1,] "RIN"     "0.420502645502646" "0.724044583696066" "0.68338517747747"
> # [2,] "DegFact" "0.876516605981734" "0.643613928123002" "0.521618857725795"
> # Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size
> # [1,] "0.627829396038413"  "4"            "4"            "8"
> # [2,] "0.737191191352892"  "8"            "5"            "3"
> dataFrame <- qualityRange(data=rnaMetrics, k.range=c(2,4), seed = 20, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
Processing metric: DegFact(2)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
> assay(getDataQualityRange(dataFrame, 2))
  Metric    Cluster_1_SilScore  Cluster_2_SilScore  Avg_Silhouette_Width
1 "RIN"     "0.583166775069983" "0.619872562681118" "0.608402004052639" 
2 "DegFact" "0.664573423022171" "0.675315791048653" "0.666587617027136" 
  Cluster_1_Size Cluster_2_Size
1 "5"            "11"          
2 "13"           "3"           
> # Metric    Cluster_1_SilScore  Cluster_2_SilScore  Avg_Silhouette_Width Cluster_1_Size
> # 1 "RIN"     "0.583166775069983" "0.619872562681118" "0.608402004052639"  "5"
> # 2 "DegFact" "0.664573423022171" "0.675315791048653" "0.666587617027136"  "13"
> # Cluster_2_Size
> # 1 "11"
> # 2 "3"
> assay(getDataQualityRange(dataFrame, 4))
  Metric    Cluster_1_SilScore  Cluster_2_SilScore  Cluster_3_SilScore 
1 "RIN"     "0.420502645502646" "0.674226581940152" "0.433333333333333"
2 "DegFact" "0.759196481622952" "0.59496499852177"  "0.600198799385732"
  Cluster_4_SilScore  Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size
1 "0.348714574898785" "0.463905611516569"  "4"            "4"           
2 "0.521618857725795" "0.634170498361632"  "5"            "3"           
  Cluster_3_Size Cluster_4_Size
1 "3"            "5"           
2 "5"            "3"           
> # Metric    Cluster_1_SilScore  Cluster_2_SilScore  Cluster_3_SilScore
> # 1 "RIN"     "0.420502645502646" "0.674226581940152" "0.433333333333333"
> # 2 "DegFact" "0.759196481622952" "0.59496499852177"  "0.600198799385732"
> # Cluster_4_SilScore  Avg_Silhouette_Width Cluster_1_Size Cluster_2_Size Cluster_3_Size
> # 1 "0.348714574898785" "0.463905611516569"  "4"            "4"            "3"
> # 2 "0.521618857725795" "0.634170498361632"  "5"            "3"            "5"
> # Cluster_4_Size
> # 1 "5"
> # 2 "3"
> dataFrame1 <- qualitySet(data=rnaMetrics, k.set=c(2,3,4), getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
Processing metric: DegFact(2)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
> 
> 
> dataFrame <- metricsCorrelations(data=rnaMetrics, getImages = FALSE, margins = c(4,4,11,10))

Data loaded.
Number of rows: 16
Number of columns: 3


> assay(dataFrame, 1)
               RIN    DegFact
RIN      1.0000000 -0.9744685
DegFact -0.9744685  1.0000000
> 
> 
> dataFrame <- stability(data=rnaMetrics, cbi="kmeans", k=2, bs=100, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
Processing metric: DegFact(2)
	Calculation of k = 2
> dataFrame <- stability(data=rnaMetrics, cbi="clara", k=2, bs=100, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
Processing metric: DegFact(2)
	Calculation of k = 2
> dataFrame <- stability(data=rnaMetrics, cbi="clara_pam", k=2, bs=100, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
Processing metric: DegFact(2)
	Calculation of k = 2
> dataFrame <- stability(data=rnaMetrics, cbi="hclust", k=2, bs=100, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
Processing metric: DegFact(2)
	Calculation of k = 2
> dataFrame <- stability(data=rnaMetrics, cbi="pamk", k=2, bs=100, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
Processing metric: DegFact(2)
	Calculation of k = 2
> dataFrame <- stability(data=rnaMetrics, cbi="pamk_pam", k=2, bs=100, getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
Processing metric: DegFact(2)
	Calculation of k = 2
> 
> # Supported CBIs:
> evaluomeRSupportedCBI()
[1] "kmeans"    "clara"     "clara_pam" "hclust"    "pamk"      "pamk_pam" 
> 
> dataFrame <- qualityRange(data=rnaMetrics, k.range=c(2,10), getImages = FALSE)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
	Calculation of k = 5
	Calculation of k = 6
	Calculation of k = 7
	Calculation of k = 8
	Calculation of k = 9
	Calculation of k = 10
Processing metric: DegFact(2)
	Calculation of k = 2
	Calculation of k = 3
	Calculation of k = 4
	Calculation of k = 5
	Calculation of k = 6
	Calculation of k = 7
	Calculation of k = 8
	Calculation of k = 9
	Calculation of k = 10
> dataFrame
ExperimentList class object of length 9:
 [1] k_2: SummarizedExperiment with 2 rows and 6 columns
 [2] k_3: SummarizedExperiment with 2 rows and 8 columns
 [3] k_4: SummarizedExperiment with 2 rows and 10 columns
 [4] k_5: SummarizedExperiment with 2 rows and 12 columns
 [5] k_6: SummarizedExperiment with 2 rows and 14 columns
 [6] k_7: SummarizedExperiment with 2 rows and 16 columns
 [7] k_8: SummarizedExperiment with 2 rows and 18 columns
 [8] k_9: SummarizedExperiment with 2 rows and 20 columns
 [9] k_10: SummarizedExperiment with 2 rows and 22 columns
> 
> #dataFrame <- stabilityRange(data=rnaMetrics, k.range=c(2,8), bs=20, getImages = FALSE)
> #assay(dataFrame)
> 
> proc.time()
   user  system elapsed 
 10.307   0.502  10.794 

evaluomeR.Rcheck/tests/testAnalysis.Rout


R version 4.1.1 (2021-08-10) -- "Kick Things"
Copyright (C) 2021 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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(evaluomeR)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats

Attaching package: 'MatrixGenerics'

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

    colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
    colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
    colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
    colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
    colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
    colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
    colWeightedMeans, colWeightedMedians, colWeightedSds,
    colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
    rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
    rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
    rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
    rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
    rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
    rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
    rowWeightedSds, rowWeightedVars

Loading required package: GenomicRanges
Loading required package: stats4
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, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'Biobase'

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

    rowMedians

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

    anyMissing, rowMedians

Loading required package: MultiAssayExperiment
Loading required package: cluster
Loading required package: fpc
Loading required package: randomForest
randomForest 4.6-14
Type rfNews() to see new features/changes/bug fixes.

Attaching package: 'randomForest'

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

    combine

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

    combine

Loading required package: flexmix
Loading required package: lattice
> 
> data("rnaMetrics")
> plotMetricsMinMax(rnaMetrics)
There were 17 warnings (use warnings() to see them)
> plotMetricsBoxplot(rnaMetrics)
Warning messages:
1: Use of `data.melt$variable` is discouraged. Use `variable` instead. 
2: Use of `data.melt$value` is discouraged. Use `value` instead. 
> cluster = plotMetricsCluster(ontMetrics, scale = TRUE)
> plotMetricsViolin(rnaMetrics)
Warning messages:
1: Use of `data.melt$variable` is discouraged. Use `variable` instead. 
2: Use of `data.melt$value` is discouraged. Use `value` instead. 
3: Use of `data.melt$variable` is discouraged. Use `variable` instead. 
4: Use of `data.melt$value` is discouraged. Use `value` instead. 
> 
> stabilityData <- stabilityRange(data=rnaMetrics, k.range=c(3,4), bs=20, getImages = FALSE, seed=100)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 3
	Calculation of k = 4
Processing metric: DegFact(2)
	Calculation of k = 3
	Calculation of k = 4
> qualityData <- qualityRange(data=rnaMetrics, k.range=c(3,4), getImages = FALSE, seed=100)

Data loaded.
Number of rows: 16
Number of columns: 3


Processing metric: RIN(1)
	Calculation of k = 3
	Calculation of k = 4
Processing metric: DegFact(2)
	Calculation of k = 3
	Calculation of k = 4
> 
> kOptTable <- getOptimalKValue(stabilityData, qualityData, k.range=c(3,4))
Processing metric: RIN

	Maximum stability and quality values matches the same K value: '3'

Processing metric: DegFact

	Maximum stability and quality values matches the same K value: '3'

> kOptTable
   Metric Stability_max_k Stability_max_k_stab Stability_max_k_qual
1     RIN               3            0.8901389            0.6278294
2 DegFact               3            1.0000000            0.7371912
  Quality_max_k Quality_max_k_stab Quality_max_k_qual Global_optimal_k
1             3          0.8901389          0.6278294                3
2             3          1.0000000          0.7371912                3
> 
> 
> df = assay(rnaMetrics)
> k.vector1=rep(5,length(colnames(df))-1)
> k.vector2=rep(2,length(colnames(df))-1)
> 
> plotMetricsClusterComparison(rnaMetrics, k.vector1=k.vector1, k.vector2=k.vector2)
> plotMetricsClusterComparison(rnaMetrics, k.vector1=3, k.vector2=c(2,5))
> 
> 
> proc.time()
   user  system elapsed 
  8.639   0.345   8.969 

Example timings

evaluomeR.Rcheck/evaluomeR-Ex.timings

nameusersystemelapsed
evaluomeRSupportedCBI000
getDataQualityRange0.4420.0040.446
getOptimalKValue0.5050.0040.509
globalMetric1.8030.1121.915
metricsCorrelations0.0410.0110.052
plotMetricsBoxplot0.3630.0080.371
plotMetricsCluster0.1660.0090.175
plotMetricsClusterComparison0.3890.0030.393
plotMetricsMinMax0.2570.0010.256
plotMetricsViolin0.5150.0190.535
quality0.2100.0070.218
qualityRange0.2460.0040.251
qualitySet0.0610.0000.061
stability1.9610.0311.993
stabilityRange2.3990.0242.423
stabilitySet0.3870.0080.395