\name{baf2mbaf}
\alias{baf2mbaf}
\title{Calculate mBAF from BAF}
\usage{
  baf2mbaf(baf, hom.cutoff = 0.95, calls = NULL,
    call.pairs = NULL)
}
\arguments{
  \item{baf}{numeric matrix of BAF values}

  \item{hom.cutoff}{numeric, values above this cutoff to be
  made NA (considered HOM)}

  \item{calls}{matrix of NA, CT, AG, etc. genotypes to
  select HETs (in normals). Dimnames must match baf
  matrix.}

  \item{call.pairs}{list, names represent target samples
  for HOMs to set to NA. Values represent columns in
  "calls" matrix.}
}
\value{
  numeric matix of mBAF values
}
\description{
  Calculate Mirrored B-Allele Frequence (mBAF) from
  B-Allele Frequency (BAF) as in Staaf et al., Genome
  Biology, 2008.  BAF is converted to mBAF by folding
  around 0.5 so that is then between 0.5 and 1. HOM value
  are then made NA to leave only HET values that can be
  easily segmented. Values > hom.cutoff are made NA. Then,
  if genotypes (usually from a matched normal) are provided
  as the matrix 'calls' additional HOMs can be set to NA.
  The argument 'call.pairs' is used to match columns in
  'calls' to columns in 'baf'.
}
\examples{
data(genoset)
   mbaf = baf2mbaf( baf(baf.ds), hom.cutoff=0.9 )
   calls = matrix(sample(c("AT","AA","CG","GC","AT","GG"),(nrow(baf.ds) * 2),replace=TRUE),ncol=2,dimnames=list(featureNames(baf.ds),c("K","L")))
   mbaf = baf2mbaf( baf(baf.ds), hom.cutoff=0.9, calls = calls, call.pairs = list(K="L",L="L") ) # Sample L is matched normal for tumor sample K, M only uses hom.cutoff
   assayDataElement(baf.ds,"mbaf") = baf2mbaf( baf(baf.ds), hom.cutoff=0.9 ) # Put mbaf back into the BAFSet object as a new element
}
\author{
  Peter M. Haverty
}