calKaKs: calKaKs calculates the Ka/Ks of each group

In qingjian1991/MPTevol: Clonal Evolutionary History and Metastatic Routines Analysis for Multiple Primary Tumors

calKaKs calculates the Ka/Ks of each group

Description

The mutations are classified by classifyMut() internally.

Usage

calKaKs(
  maf,
  patient.id = NULL,
  class = "SP",
  classByTumor = FALSE,
  vaf.cutoff = 0.05,
  parallel = TRUE
)

Arguments

maf	Maf or MafList object generated by readMaf() function
patient.id	Select the specific patients. Default NULL, all patients are included.
class	The class which would be represented. "SP" (Shared pattern: Public/Shared/Private), other options: "CS" (Clonal status: Clonal/Subclonl) and "SPCS". see MesKit::classifyMut().
vaf.cutoff	Removing mutations with low variant allele frequency (VAF).
parallel	If TRUE (default), run in parallel.

Examples

library(MesKit)
data.type <- "split1"

maf <- readMaf(
  mafFile = system.file(package = "MPTevol", "extdata", sprintf("meskit.%s.mutation.txt", data.type)),
  ccfFile = system.file(package = "MPTevol", "extdata", sprintf("meskit.%s.CCF.txt", data.type)),
  clinicalFile = system.file(package = "MPTevol", "extdata", sprintf("meskit.%s.clinical.txt", data.type)),
  refBuild = "hg19",
  ccf.conf.level = 0.95
)

# calKaKas
kaks <- calKaKs(maf, patient.id = "Breast", class = "SP", parallel = TRUE, vaf.cutoff = 0.05)
kaks
kaks <- calKaKs(maf, patient.id = "Breast", class = "CS", parallel = TRUE, vaf.cutoff = 0.05)
kaks
kaks <- calKaKs(maf, class = "SP", parallel = TRUE, vaf.cutoff = 0.05)
kaks

qingjian1991/MPTevol documentation built on Jan. 30, 2023, 10:16 p.m.