run_facets: Run FACETS

In mskcc/facets-suite: Functions to run and parse output from FACETS

Run FACETS

Description

Runs FACETS on an input count file, with specified parameter settings.

Usage

run_facets(read_counts, cval = 100, diplogr = NULL, ndepth = 35,
  snp_nbhd = 250, min_nhet = 15, genome = c("hg18", "hg19", "hg38",
  "mm9", "mm10"), seed = 100)

Arguments

read_counts	Read counts object, generated by 'snp-pileup'.
cval	Segmentation parameter, higher values for higher sensitivity.
diplogr	Manual dipLogR value, if left empty 'facets' finds the most likely sample baseline.
ndepth	Minimum depth in normal to retain SNP, see 'facets' help.
snp_nbhd	Minimum basepair distance for SNPs, see 'facets' help.
min_nhet	Minimum number of heterozygous SNPs on segment required for clustering, see 'facets' help.
genome	Genome build.
seed	Seed value for random number generation, set to enable full reproducibility.

Value

A list object containing the following items. See FACETS documentation for more details:

• snps: SNPs used for copy-number segmentation, het==1 for heterozygous loci.

• segs: Inferred copy-number segmentation.

• purity: Inferred sample purity, i.e. fraction of tumor cells of the total cellular population.

• ploidy: Inferred sample ploidy.

• diplogr: Inferred dipLogR, the sample-specific baseline corresponding to the diploid state.

• alballogr: Alternative dipLogR value(s) at which a balanced solution was found.

• flags: Warning flags from the naïve segmentation algorithm.

• em_flags: Warning flags from the expectation-maximization segmentation algorithm.

• loglik: Log-likelihood value of the fitted model.

Examples

## Not run: 
library(pctGCdata)
run_facets(test_read_counts, cval = 500, genome = 'hg38')

## End(Not run)

mskcc/facets-suite documentation built on Sept. 13, 2022, 4:14 a.m.