BISEP_cv: BISEP_cv

In chapmandu2/CollateralVulnerability2016: Collateral Vulnerability Pipeline

Description

Input a matrix of continuous data with genes as rows and samples as columns. Algorithm may take some considerable time to run (1 hour for 20,500 genes across 800 samples)

Usage

BISEP_cv(data = data, seed_val = NULL)

Arguments

data	This should be a log2 gene expression matrix with genes as rownames and samples as column names. Suitable for gene expression data from any platform - NGS datasets should be RPKM or RSEM values.
seed_val	A numeric. Default is NULL - seed not set.

Details

Note: this is a slightly modified version of the BISEP algorithm from the BiSEp package: see the original BISEP function documentation. The modification allows the random seed to be set so that p-values generated by sampling stay the same from run to run.

Value

A list containing three matrices. Matrix 1 contains the output of the BISEP algorithm - including the midpoint of the bimodal distribution and the associated p value. Matrix 2 contains the output from the BI algorithm - including the delta, pi and BI values. Matrix 3 contains the input matrix.

Author(s)

Mark Wappett, m.a.wappett at googlemail.com

References

Wappett et al BMC Genomics 2016

See Also

BiSEp

Examples

library(BiSEp)
data("INPUT_data")
bisep_out <- BISEP_cv(INPUT_data, seed_val = 12345)
bisep_out$BISEP
bisep_out$BI

chapmandu2/CollateralVulnerability2016 documentation built on May 13, 2019, 3:27 p.m.