TrackSig: Determine an evolutionary trajectory.

In morrislab/TrackSigFreq: TrackSig - cancer evolutionary trajectory estimation

Description

TrackSig will take an input VCF file and corresponding annotation, and determine an eveolutionary trajectory for the sample, based on changepoints found using the PELT segmentation algorithm.

Usage

TrackSig(
  vcfFile,
  activeInSample,
  cnaFile = NULL,
  purity = 1,
  sampleID = NULL,
  referenceSignatures = TrackSig:::alex_merged,
  scoreMethod = "SigFreq",
  binSize = 100,
  nCutoff = 10000,
  desiredMinSegLen = 1,
  refGenome = BSgenome.Hsapiens.UCSC.hg19::BSgenome.Hsapiens.UCSC.hg19
)

Arguments

vcfFile	path to variant calling format (vcf) file
activeInSample	list of signatures names to fit the exposures of. All listed signatures must be present in the referenceSignatures dataframe.
cnaFile	path to copy number abberation (cna) file. If not provided, all copy numbers default to 2.
purity	number between 0 and 1 of the percentage of cells in the sample that are cancerous
sampleID	name to call sample. If none provided, name will be automatically drawn from the provided vcf file name.
referenceSignatures	dataframe containing definitions of mutational signatures.
scoreMethod	string to indicate what scoring method to apply when finding changepoints. Options are "Signature", "SigFreq" and "Frequency"
binSize	number of mutations per bin (default 100)
nCutoff	maximum number of total mutations to consider (samples with more than nCutoff muations will be down-sampled)
desiredMinSegLen	minimum number of mutations to include in a PELT segment (the desiredMinSegLen will be overridden if there are too few for accurate scoring)
refGenome	BSgenome to use as reference

morrislab/TrackSigFreq documentation built on July 5, 2021, 6:33 a.m.