contextSNV: Partition mutations according to their genomic contexts
In sjdlabgroup/MutSigTools: Mutational signature analysis

Description Usage Arguments Details Value See Also Examples

Group mutations according to their occurrence within or outside user-annotated genomic segments.

1 2	contextSNV(snv, file = "empty", mode = "include", bed_file_start_cord = 0)

`snv`	A dataframe having sample, chr, pos, ref, alt and/or freq as its columns.
`file`	Path of the BED file, having genomic segments and their context information. This snv dataframe can be generated by `vcfToSNV`.
`mode`	Default is set to include: Select mutations lying inside the given genomic contexts (obtained from BED file). exclude: will give mutations outside the given context.
`bed_file_start_cord`	Default: 0: If BED file has 0-based cordinate system. 1: If BED file has 1-based cordinate system.

When the include mode is used, group mutations according to their occurrence in user-specifiedannotated genomic segments; such segments could represent specific genomic or epigenomic contexts (e.g.actively transcribed coding regions). Alternately, in the exclude mode, mutations in undesired regions (e.g.black-listed genomic regions) can be removed.

snv dataframe with column names of sample, chr, pos, ref, alt, freq. Where, sample name will be concatenated by the its genomic context. Example: if a mutation within a sample of name sample1, lies in the context segment of label C1 given in the input bed file , the sample name of mutation is modified to sample1_C1. The mutations that don't lie in any context segment given in the BED file are discarded.

vcfToSNV to generate snv dataframe, and https://genome.ucsc.edu/FAQ/FAQformat.html for BED file format.

BED_file=system.file("extdata", "context_testFile.bed", package = "MutSigTools", mustWork = TRUE)

data(snv_sample.rda)   # load 'snv' dataframe object

context_snv=contextSNV(snv=snv_sample,BED_file, mode='include', bed_file_start_cord=0)