vivlib: An R package for useful bioinformatics wrappers

Description Usage Arguments Value Examples

Plot heatmap of raw counts for top DEgenes using edgeR/DESeq2 output

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plotHeatmap(DEoutput, fdr = 0.05, fcountOutput, sampleNames,
  topNgenes = 100, clusterbyCorr = FALSE, useGeneNames = TRUE,
  markGenes = NULL, outFile = NA)

`DEoutput`	A tab-seperated edgeR/DESeq2 output file, using `EdgeR_wrapper` or `DESeq_wrapper`
`fdr`	FDR cutoff for DE genes
`fcountOutput`	Featurecounts output (for raw counts)
`sampleNames`	samplenames for heatmap column label (must be the same order as in featurecounts file)
`topNgenes`	How many genes to plot. Type NULL for all genes (might take long time)
`clusterbyCorr`	Whether to cluster row/columns by correlations. Default is eucledian distances.
`useGeneNames`	Use gene names to plot instead of default geneIDs. only works if the input has been annotated by `annotate_DEoutput` function.
`markGenes`	Genes to mark in bold on heatmap.
`outFile`	File name to save the output. NULL prints heatmap on screen.

A heatmap.

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deout <- system.file("extdata", "edgeR_output_annotated.tsv", package="vivlib")
fc <- system.file("extdata", "fcount_mouse.tsv", package="vivlib")
plotHeatmap(DEoutput = deout, fcountOutput = fc, sampleNames = rep(c("cnt","KD"), each = 3))