persistSig: Mutation signatures in different allele frequency spectrum
In sjdlabgroup/MutSigTools: Mutational signature analysis

Description Usage Arguments Value See Also Examples

Determine the burden of different mutation signatures acrross different allele frequency ranges.The function should be used with caution; Local copy number and purity-corrected variant allele frequencies should be provided in the column 6 of the snv

1 2	persistSig(snv, th_vec_lw, th_vec_up, signatures.ref = signatures.cosmic, bsg = BSgenome.Hsapiens.UCSC.hg19::Hsapiens)

`snv`	A dataframe having sample, chr, pos, ref, alt and/or freq as it's columns. This dataframe may have more than one sample.
`th_vec_lw`	A vector of lower limits of frequency ranges.
`th_vec_up`	A vector of upper limits of frequency ranges.
`signatures.ref`	An object of class mutsig comprising the set of signatures. (signatures.nature2013 or signatures.cosmic or signatures.cosmic.2019 ), Default: 'signatures.cosmic'
`bsg`	An object of class BSGenome. Default: BSgenome.Hsapiens.UCSC.hg19

A list of samples having mutational signature corresponding to each allele frequency range

vcfToSNV to generate snv dataframe.

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data(snv_sample)   # load 'snv' dataframe object
mut_sig_per_freq_range=persistSig(snv=snv_sample,th_vec_lw=c(0,0.4), th_vec_up=c(0.1,1), signatures.ref = signatures.cosmic,  bsg=BSgenome.Hsapiens.UCSC.hg19::Hsapiens)  # list of samples having mutational signature for each allele frequency range i.e., in our example (0.0 - 0.1) & (0.4 - 1.0).