plots {EnrichmentBrowser} | R Documentation

## Visualization of gene expression

### Description

Visualization of differential gene expression via heatmap, p-value histogram and volcano plot (fold change vs. p-value).

### Usage

    pdistr(p)

    volcano(fc, p)

    exprsHeatmap(expr, grp, scale.rows = TRUE)

### Arguments

`p` | Numeric vector of p-values for each gene.
`fc` | Numeric vector of fold changes (typically on log2 scale).
`expr` | Expression matrix. Rows correspond to genes, columns to samples.
`grp` | *BINARY* group assignment for the samples. Use '0' and '1' for unaffected (controls) and affected (cases) samples, respectively.
`scale.rows` | Should rows of the expression matrix be scaled for better visibility of expression differences between sample groups? Defaults to TRUE.

### Value

None, plots to a graphics device.

### Author(s)

Ludwig Geistlinger <Ludwig.Geistlinger@sph.cuny.edu>

### See Also

`deAna` for differential expression analysis, `ComplexHeatmap::Heatmap`, and `hist` for generic plotting.

### Examples

        # (1) simulating expression data: 100 genes, 12 samples
        se <- makeExampleData(what="SE")

        # plot heatmap
        exprsHeatmap(expr=assay(se), grp=as.factor(se$GROUP))

        # (2) DE analysis
        se <- deAna(se)
        pdistr(rowData(se)$ADJ.PVAL)
        volcano(fc=rowData(se)$FC, p=rowData(se)$ADJ.PVAL)

[Package EnrichmentBrowser version 2.24.2 Index]