bcgr.lawrence: Background mutation rate based on Lawrence's background...

In hanasusak/cDriver: Find best driver candidate genes

Description

bcgr.lawrence function calculates the background probability that a gene is mutated based on the background somatic mutation rate provided in the Lawrence paper.

Usage

bcgr.lawrence(sample.mutations, genes = NULL, lengthGenes = NULL,
  Variant_Classification = NULL, Hugo_Symbol = NULL,
  Tumor_Sample_Barcode = NULL, CCF = NULL)

Arguments

sample.mutations	data frame in MAF like format. Columns names/header in sample.mutations must be: Variant_Classification : column specified in the MAF format, which distinguishes between silent and nonsilent SNVs Hugo_Symbol : column specified in the MAF format, which reports the gene name for each SNV. Tumor_Sample_Barcode : column specified in the MAF format, which reports in wich patient the SNV was found. CCF : numeric column produce by CCF function, or calculated previously for each SNV.
genes	vector of genes which were sequenced. Vector of unique values of Hugo_Symbol names (with possibility of more additional genes which did not have any SNV in the cohort). Default is NULL value and then the list of the unique genes is taken from sample.mutations.
lengthGenes	numeric vector of the lengths (suquenced) for all genes. Vector should have the same order as given in the variable genes. Default is NULL value and then the length of the genes is taken from data set length.genes (form package cDriver) as defined in column length. If a gene is not found in this data frame, then the median value is taken from the gene list provided by default.
Variant_Classification	(optional) integer/numeric value indicating which column in sample.mutations contains the classification for the SNVs (Silent or not). Default is NULL value (in this case sample.mutations should already have this column). Column with this name should not already exist in sample.mutations.
Hugo_Symbol	(optional) integer/numeric value indicating which column in sample.mutations contains the gene names for the SNVs. Default is NULL value (in this case sample.mutations should already have this column) Column with this name should not already exist in sample.mutations.
Tumor_Sample_Barcode	(optional) integer/numeric value indicating which column in sample.mutations contains the sample ids for the SNVs. Default is NULL value (in this case sample.mutations should already have this column) Column with this name should not already exist in sample.mutations.
CCF	(optional) integer/numeric value indicating which column in sample.mutations contains the cancer cell fraction information for the SNVs. Default is NULL value (in this case sample.mutations should already have this column) Column with this name should not already exist in sample.mutations.

Details

Function uses sample.mutations to estimate the expected number of nonsilent mutations per patient.

Value

a numeric vector of the probabilites that a gene has a nonsilent mutation (not caused by cancer).

References

http://www.ncbi.nlm.nih.gov/pubmed/23770567.

Examples

bcgr.L <- bcgr.lawrence(sample.genes.mutect, length.genes$Hugo_Symbol, length.genes$Coverd_len)
head(bcgr.L)

hanasusak/cDriver documentation built on May 17, 2019, 2:27 p.m.