calNeiDist: calNeiDist

In MesKit: A tool kit for dissecting cancer evolution from multi-region derived tumor biopsies via somatic alterations

Description

Nei's distance of CCF for sample/tumor pair.

Usage

calNeiDist(
  maf,
  patient.id = NULL,
  withinTumor = FALSE,
  min.ccf = 0,
  plot = TRUE,
  use.circle = TRUE,
  title = NULL,
  number.cex = 8,
  number.col = "#C77960",
  use.tumorSampleLabel = FALSE,
  ...
)

Arguments

maf	A Maf or MafList object generated by readMaf function.
patient.id	Select the specific patients. Default NULL, all patients are included.
withinTumor	Calculate between-region heterogeneity within tumor. (Default: FALSE).
min.ccf	Specify the minimum CCF. Default 0.
plot	Logical (Default: TRUE).
use.circle	Logical (Default: TRUE). Whether to use "circle" as visualization method of correlation matrix.
title	The title of the plot. Default "Nei's distance"
number.cex	The size of text shown in correlation plot. Default 8.
number.col	The color of text shown in correlation plot. Default "#C77960".
use.tumorSampleLabel	Logical (Default: FALSE). Rename the 'Tumor_Sample_Barcode' by 'Tumor_Sample_Label'.
...	Other options passed to subMaf

Value

Nei's genetic distance matrix and heatmap of sample-pairs from the same patient

References

Lee JK, Wang J, Sa JK, et al. Spatiotemporal genomic architecture informs precision oncology in glioblastoma. Nat Genet. 2017;49(4):594-599.

Examples

maf.File <- system.file("extdata/", "CRC_HZ.maf", package = "MesKit")
clin.File <- system.file("extdata/", "CRC_HZ.clin.txt", package = "MesKit")
ccf.File <- system.file("extdata/", "CRC_HZ.ccf.tsv", package = "MesKit")
maf <- readMaf(mafFile=maf.File, clinicalFile = clin.File, ccfFile=ccf.File, refBuild="hg19")
calNeiDist(maf)

MesKit documentation built on March 28, 2021, 6 p.m.