biasPlot-methods: Methods for Function 'biasPlot' in Package 'EDASeq'

In EDASeq: Exploratory Data Analysis and Normalization for RNA-Seq

Description

biasPlot produces a plot of the lowess regression of the counts on a covariate of interest, tipically the GC-content or the length of the genes.

Methods

signature(x = "matrix", y = "numeric")

It plots a line representing the regression of every column of the matrix x on the numeric covariate y. One can pass the usual graphical parameters as additional arguments (see par).

signature(x = "SeqExpressionSet", y = "character")

It plots a line representing the regression of every lane in x on the covariate specified by y. y must be one of the column of the featureData slot of the x object. One can pass the usual graphical parameters as additional arguments (see par). The parameter color_code (optional) must be a number specifying the column of phenoData to be used for color-coding. By default it is color-coded according to the first column of phenoData. If legend=TRUE and col is not specified a legend with the information stored in phenoData is added.

Examples

library(yeastRNASeq)
data(geneLevelData)
data(yeastGC)

sub <- intersect(rownames(geneLevelData), names(yeastGC))

mat <- as.matrix(geneLevelData[sub,])

data <- newSeqExpressionSet(mat,
                            phenoData=AnnotatedDataFrame(
                                      data.frame(conditions=factor(c("mut", "mut", "wt", "wt")),
                                                 row.names=colnames(geneLevelData))),
                            featureData=AnnotatedDataFrame(data.frame(gc=yeastGC[sub])))

biasPlot(data,"gc",ylim=c(0,5),log=TRUE)

EDASeq documentation built on Nov. 8, 2020, 8:29 p.m.