ccfAUC {MesKit} | R Documentation

## ccfAUC

### Description

The tumor heterogeneity was estimated as the area under the curve (AUC) of the cumulative density function from all cancer cell fractions per tumor

### Usage

    ccfAUC(
      maf,
      patient.id = NULL,
      min.ccf = 0,
      withinTumor = FALSE,
      plot.density = TRUE,
      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.
`min.ccf` | The minimum value of CCF. Default 0.
`withinTumor` | Calculate between-region heterogeneity within tumor. Default FALSE.
`plot.density` | Whether to show the density plot. Default TRUE.
`use.tumorSampleLabel` | Logical (Default: FALSE). Rename the 'Tumor_Sample_Barcode' by 'Tumor_Sample_Label'.
`...` | Other options passed to `subMaf`

### Value

A list containing AUC of CCF and a graph

### References

Charoentong P, Finotello F, et al. Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade. Cell reports 2017, 18:248-262.

### 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")
    ccfAUC(maf)

[Package MesKit version 1.4.0 Index]