betabinLRT: ShearwaterML
In deepSNV: Detection of subclonal SNVs in deep sequencing data.

Description Usage Arguments Value Author(s) References Examples

Maximum likelihood version of Shearwater producing p-values instead of Bayes factors.

betabinLRT(
  counts,
  rho = NULL,
  truncate = 0.05,
  rho.min = 1e-04,
  rho.max = 0.8,
  maxvaf = 0.3,
  mindepth = 10,
  maxtruncate = 0.5
)

`counts`	The array of counts typically generated by loadAllData.
`rho`	Use this variable to fix the dispersion parameter to a value of interest. Default: NULL, rho will be estimated from the data.
`truncate`	Samples with variant allele frequencies higher than "truncate" will be excluded from the background error model.
`rho.min`	If rho=NULL, rho will be estimated from the data in the interval [rho.min,rho.max].
`rho.max`	If rho=NULL, rho will be estimated from the data in the interval [rho.min,rho.max].
`maxvaf`	Sites with an average rate of mimatches higher than maxvaf will not be considered (e.g. SNPs or reference sites).
`mindepth`	Minimum coverage required to test a site.
`maxtruncate`	Maximum number of samples that can be excluded from the background error model by truncate for a site to be tested.

A list with two arrays for P- and Q-values.

Inigo Martincorena and Moritz Gerstung

Martincorena I, Roshan A, Gerstung M, et al. (2015). High burden and pervasive positive selection of somatic mutations in normal human skin. _Science_ (Under consideration).