topGeneQuants: Identify genes that meet pre-specified quantiles

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

Description

This function allows you to subset genes that are above pre-specified quantiles and that most closely resemble the distribution of oncogenes.

Usage

topGeneQuants(mmParams, deltMu2Thr = 90, deltMu1Thr = 10, siThr = 0.99)

Arguments

mmParams	The output from the mixModelParams function.
deltMu2Thr	The percentile threshold for the deltaMu2 statistic. All genes exceeding this percentile threshold will be selected.
deltMu1Thr	The percentile threshold for the deltaMu1 statistic. All genes exceeding this percentile threshold will be selected.
siThr	The threshold for the selectivity index statistic (between 0-1). All genes exceeding this threshold will be selected.

Value

Returns a dataframe containing all genes meeting the prespecified thresholds.

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)
topGeneQuants(mmParams)

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