calNeiDist {MesKit} | R Documentation

## calNeiDist

### 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)

[Package MesKit version 1.4.0 Index]