Methods for Function plotRLE in Package EDASeq

Description

plotRLE produces a Relative Log Expression (RLE) plot of the counts in x

Usage

plotRLE(x, ...)

Arguments

Details

The Relative Log Expression (RLE) plot is a useful diagnostic plot to visualize the differences between the distributions of read counts across samples.

It shows the boxplots of the log-ratios of the gene-level read counts of each sample to those of a reference sample (defined as the median across the samples). Ideally, the distributions should be centered around the zero line and as tight as possible. Clear deviations indicate the need for normalization and/or the presence of outlying samples.

Methods

signature(x = "matrix")

signature(x = "SeqExpressionSet")

Examples

library(yeastRNASeq)
data(geneLevelData)

mat <- as.matrix(geneLevelData)

data <- newSeqExpressionSet(mat,
                            phenoData=AnnotatedDataFrame(
                                      data.frame(conditions=factor(c("mut", "mut", "wt", "wt")),
                                                 row.names=colnames(geneLevelData))))


plotRLE(data, col=rep(2:3, each=2))

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(EDASeq)
Loading required package: Biobase
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, xtabs

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

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, 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, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

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

Loading required package: ShortRead
Loading required package: BiocParallel
Loading required package: Biostrings
Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

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

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: XVector
Loading required package: Rsamtools
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: GenomicAlignments
Loading required package: SummarizedExperiment
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/EDASeq/plotRLE-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotRLE-methods
> ### Title: Methods for Function 'plotRLE' in Package 'EDASeq'
> ### Aliases: plotRLE plotRLE-methods plotRLE,matrix-method
> ###   plotRLE,SeqExpressionSet-method
> ### Keywords: methods
> 
> ### ** Examples
> 
> library(yeastRNASeq)
> data(geneLevelData)
> 
> mat <- as.matrix(geneLevelData)
> 
> data <- newSeqExpressionSet(mat,
+                             phenoData=AnnotatedDataFrame(
+                                       data.frame(conditions=factor(c("mut", "mut", "wt", "wt")),
+                                                  row.names=colnames(geneLevelData))))
> 
> 
> plotRLE(data, col=rep(2:3, each=2))
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>