plots {EnrichmentBrowser} | R Documentation |
Visualization of differential gene expression via heatmap, p-value histogram and volcano plot (fold change vs. p-value).
pdistr(p) volcano(fc, p) exprsHeatmap(expr, grp, scale.rows = TRUE)
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. |
None, plots to a graphics device.
Ludwig Geistlinger <Ludwig.Geistlinger@sph.cuny.edu>
deAna
for differential expression analysis,
ComplexHeatmap::Heatmap
, and hist
for generic plotting.
# (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)