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### Running command:
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###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD check --install=check:evaluomeR.install-out.txt --library=/Library/Frameworks/R.framework/Versions/Current/Resources/library --no-vignettes --timings evaluomeR_1.4.0.tar.gz
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* using log directory ‘/Users/biocbuild/bbs-3.11-bioc/meat/evaluomeR.Rcheck’
* using R version 4.0.3 (2020-10-10)
* using platform: x86_64-apple-darwin17.0 (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 ‘1.4.0’
* package encoding: UTF-8
* 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 ‘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 ... 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 files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                user system elapsed
stabilityRange 4.803  0.362   5.171
* 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: 1 NOTE
See
  ‘/Users/biocbuild/bbs-3.11-bioc/meat/evaluomeR.Rcheck/00check.log’
for details.

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### Running command:
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###   /Library/Frameworks/R.framework/Versions/Current/Resources/bin/R CMD INSTALL evaluomeR
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* installing to library ‘/Library/Frameworks/R.framework/Versions/4.0/Resources/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)

R version 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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(evaluomeR)
Loading required package: SummarizedExperiment
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, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    expand.grid

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")'.

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 objects are masked from 'package:base':

    aperm, apply, rowsum

Loading required package: MultiAssayExperiment
Loading required package: cluster
Loading required package: fpc
> 
> data("rnaMetrics")
> 
> dataFrame <- stability(data=rnaMetrics, k=2, bs=100, getImages = FALSE)
Processing metric: RIN(1)
	Calculation of k = 2
Processing metric: DegFact(2)
	Calculation of k = 2
> dataFrame <- stabilityRange(data=rnaMetrics, k.range=c(2,4), bs=20, getImages = FALSE)
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 <- stabilitySet(data=rnaMetrics, k.set=c(2,3,4), bs=20, getImages = FALSE)
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, k=3, getImages = FALSE)
Processing metric: RIN(1)
	Calculation of k = 3
Processing metric: DegFact(2)
	Calculation of k = 3
> dataFrame <- qualityRange(data=rnaMetrics, k.range=c(2,4), getImages = FALSE)
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), 1)
  Metric    Cluster_1_SilScore  Cluster_2_SilScore  Avg_Silhouette_Width
1 "RIN"     "0.431069592245246" "0.803182811595014" "0.61712620192013"  
2 "DegFact" "0.728789163508571" "0.415236312384011" "0.630803897532146" 
  Cluster_1_Size Cluster_2_Size
1 "8"            "8"           
2 "11"           "5"           
> dataFrame1 <- qualitySet(data=rnaMetrics, k.set=c(2,3,4), getImages = FALSE)
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))
> assay(dataFrame, 1)
               RIN    DegFact
RIN      1.0000000 -0.9744685
DegFact -0.9744685  1.0000000
> 
> 
> proc.time()
   user  system elapsed 
 14.359   0.608  14.961 

R version 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (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(evaluomeR)
Loading required package: SummarizedExperiment
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, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    expand.grid

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")'.

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 objects are masked from 'package:base':

    aperm, apply, rowsum

Loading required package: MultiAssayExperiment
Loading required package: cluster
Loading required package: fpc
> 
> 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. 
> plotMetricsCluster(rnaMetrics)
> 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)
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)
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
        Stability_max_k Stability_max_k_stab Stability_max_k_qual Quality_max_k
RIN                   3            0.8901389            0.6278294             3
DegFact               3            1.0000000            0.7371912             3
        Quality_max_k_stab Quality_max_k_qual Global_optimal_k
RIN              0.8901389          0.6278294                3
DegFact          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(df, k.vector1, k.vector2)
> 
> proc.time()
   user  system elapsed 
 14.622   0.605  15.215