BEEM {BiSEp}

BEEM: Bimodal Expression Exclusive with Mutation

Description

Takes the output from the function BISEP and a discreet mutation matrix as input. The mutation matrix samples (columns) must mirror or overlap with the gene expression matrix. The data in the mutation matrix must be a discreet 'WT' or 'MUT' call based on the status of each gene with each sample. Detects mutations of genes enriched in either the high or low gene expression modes.

Usage

BEEM(
	bisepData=data, 
	mutData=mutData, 
	sampleType=c("cell_line", "cell_line_low", "patient", "patient_low"), 
	minMut=10
	)

Arguments

bisepData

This should be the output from the BISEP function.

mutData

This should be a matrix with genes rownames and samples as column names. All cells should be made up of a discreet 'WT' or 'MUT' call. There should be overlap (by sample) with the gene expression matrix.

sampleType

The type of sample being analysed. Select 'cell_line' or 'patient' for datasets with greater than ~200 samples. For datasets with less than ~200 samples, use 'cell_line_low' or 'patient_low'.

minMut

The minimum number of mutations you for a gene would consider for analysis.

Details

Lower sample numbers have more stringent bimodality hurdles to clear in order to keep the false positive rate lower. The tool returns a percentage complete text window so the user can observe the status of the job.

Value

A matrix containing 10 columns. Column 1 contains the bimodal genes from the expression data (gene 1) and column 2 contains the mutated candidate synthetic lethal gene pair (gene 2). Columns 3 and 4 contain the number of mutations of gene 2 in the low and high expression modes of gene 1. Column 5 contains the fishers p value that evaluates enrichment of mutation in either the high or low mode (indicated by column 10). Columns 6 and 7 contain the percentage of samples in the low and high expression modes of gene 1 that are mutated for gene 2. Columns 8 and 9 contain information on the overall size (in terms of sample) of the low and high expression modes of gene 1.

Author(s)

Mark Wappett