mathScore {MesKit} | R Documentation

## mathScore

### Description

calculates MATH score of each tumor sample or based on Mutant-Allele Tumor Heterogeneity (MATH) approach.

### Usage

    mathScore(
      maf,
      patient.id = NULL,
      withinTumor = FALSE,
      min.vaf = 0,
      use.adjVAF = FALSE,
      segFile = NULL,
      use.tumorSampleLabel = FALSE,
      ...
    )

### Arguments

`maf` | 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.vaf` | Specify The minimum VAF to filter variants. Default: 0.
`use.adjVAF` | Use adjusted VAF in analysis when adjusted VAF or CCF is available. Default: FALSE.
`segFile` | The segment file.
`use.tumorSampleLabel` | Logical (Default: FALSE). Rename the 'Tumor_Sample_Barcode' by 'Tumor_Sample_Label'.
`...` | Other options passed to `subMaf`

### Value

A data.frame of MATH scores

### References

Mroz, Edmund A. et al. Intra-Tumor Genetic Heterogeneity and Mortality in Head and Neck Cancer: Analysis of Data from The Cancer Genome Atlas. Ed. Andrew H. Beck. PLoS Medicine 12.2 (2015): e1001786.

### 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")
    mathScore(maf)

[Package MesKit version 1.4.0 Index]