calNeiDist {MesKit} | R Documentation |
Nei's distance of CCF for sample/tumor pair.
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, ... )
maf |
A Maf or MafList object generated by |
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 |
Nei's genetic distance matrix and heatmap of sample-pairs from the same patient
Lee JK, Wang J, Sa JK, et al. Spatiotemporal genomic architecture informs precision oncology in glioblastoma. Nat Genet. 2017;49(4):594-599.
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)