plotGeneHist: Plot a histogram of gene expression values from tumor and...

In dpique/oncomix: Identifying Genes Overexpressed in Subsets of Tumors from Tumor-Normal mRNA Expression Data

Description

This function allows you to plot a histogram of gene expression values from tumor and adjacent normal tissue with the option of including the best fitting Gaussian curve.

Usage

plotGeneHist(mmParams, exprNml, exprTum, isof)

Arguments

mmParams	The output from the getMixModelParams function.
exprNml	A dataframe (S3 or S4), matrix, or SummarizedExperiment object containing normal data with patients as columns and genes as rows.
exprTum	A dataframe (S3 or S4), matrix, or SummarizedExperiment object containing tumor data with patients as columns and genes as rows.
isof	The gene isoform to visualize

Value

Returns a histogram of the gene expression values from the two groups.

See Also

mixModelParams

Examples

exprNml <- as.data.frame(matrix(data=rgamma(n=150, shape=2, rate=2),
nrow=10, ncol=15))
colnames(exprNml) <- paste0("patientN", seq_len(ncol(exprNml)))
rownames(exprNml) <- paste0("gene", seq_len(nrow(exprNml)))

exprTum <- as.data.frame(matrix(data=rgamma(n=150, shape=4, rate=3),
nrow=10, ncol=15))
colnames(exprTum) <- paste0("patientT", seq_len(ncol(exprTum)))
rownames(exprTum) <- paste0("gene", seq_len(nrow(exprTum)))
mmParams <- mixModelParams(exprNml, exprTum)
isof <- rownames(mmParams)[1]
plotGeneHist(mmParams, exprNml, exprTum, isof)

dpique/oncomix documentation built on May 12, 2019, 2 p.m.