biasPlot-methods {EDASeq} | R Documentation |
biasPlot
in Package EDASeq 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.
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.
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)