calFst {MesKit} | R Documentation

## calFst

### Description

Genetic divergence between regions of subclonal sSNVs using the Weir and Cockerham method

### Usage

    calFst(
      maf,
      patient.id = NULL,
      min.vaf = 0,
      min.total.depth = 2,
      use.adjVAF = FALSE,
      plot = TRUE,
      withinTumor = FALSE,
      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.
`min.vaf` | Specify The minimum VAF to filter variants. Default 0.
`min.total.depth` | The minimum total allele depth for filtering variants. Default 2.
`use.adjVAF` | Use adjusted VAF in analysis when adjusted VAF or CCF is available. Default FALSE.
`plot` | Logical (Default: TRUE).
`withinTumor` | Logical (Default: FALSE). Whether calculate between-region heterogeneity within tumors.
`use.circle` | Logical (Default: TRUE). Whether use "circle" in the plot. 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

A list contains Fst value of MRS and Hudson estimator of each sample-pair, respectively.

### References

Sun R, Hu Z, Sottoriva A, et al. Between-region genetic divergence reflects the mode and tempo of tumor evolution. Nat Genet. 2017;49(7):1015-1024.

Bhatia G, Patterson N, Sankararaman S, Price AL. Estimating and interpreting FST: the impact of rare variants. Genomic Res. 2013;23(9):1514-1521.

### 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")
    calFst(maf)

[Package MesKit version 1.4.0 Index]