EDASeq (version 2.6.2)

MDPlot-methods: Methods for Function MDPlot in Package EDASeq

Description

MDPlot produces a mean-difference smooth scatterplot of two lanes in an experiment.

Usage

MDPlot(x,y,...)

Arguments

x

Either a numeric matrix or a SeqExpressionSet object containing the gene expression.

y

A numeric vecor specifying the lanes to be compared.

...

See par

Methods

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

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

Details

The mean-difference (MD) plot is a useful plot to visualize difference in two lanes of an experiment. From a MDPlot one can see if normalization is needed and if a linear scaling is sufficient or nonlinear normalization is more effective.

The MDPlot also plots a lowess fit (in red) underlying a possible trend in the bias related to the mean expression.

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])))

MDPlot(data,c(1,3))