CHECK report for evaluomeR on malbec2
This page was generated on 2020-10-17 11:54:43 -0400 (Sat, 17 Oct 2020).
|  | TO THE DEVELOPERS/MAINTAINERS OF THE evaluomeR PACKAGE: Please make sure to use the following settings in order to reproduce any error or warning you see on this page. |  | 
 
| evaluomeR 1.4.0 José Antonio Bernabé-Díaz
 
 
| Snapshot Date: 2020-10-16 14:40:19 -0400 (Fri, 16 Oct 2020) |  | URL: https://git.bioconductor.org/packages/evaluomeR |  | Branch: RELEASE_3_11 |  | Last Commit: 6d2d310 |  | Last Changed Date: 2020-04-27 15:25:05 -0400 (Mon, 27 Apr 2020) |  | malbec2 | Linux (Ubuntu 18.04.4 LTS) / x86_64 | OK | OK | [ OK ] |  |  | 
| tokay2 | Windows Server 2012 R2 Standard / x64 | OK | OK | OK | OK |  | 
| machv2 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK |  | 
Summary
Command output
Installation output
evaluomeR.Rcheck/00install.out
Tests output
evaluomeR.Rcheck/tests/testAll.Rout
R version 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out"
Copyright (C) 2020 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: 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 
  9.458   0.409   9.853 
 evaluomeR.Rcheck/tests/testAnalysis.Rout
R version 4.0.3 (2020-10-10) -- "Bunny-Wunnies Freak Out"
Copyright (C) 2020 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: 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 
 10.000   0.369  10.357 
 
Example timings
evaluomeR.Rcheck/evaluomeR-Ex.timings