biasPlot-methods {EDASeq} | R Documentation

## Methods for Function `biasPlot` in Package EDASeq

### 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)

[Package EDASeq version 2.22.0 Index]