baf2mbaf {genoset} | R Documentation |
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'.
baf2mbaf(baf, hom.cutoff = 0.95, calls = NULL, call.pairs = NULL)
baf |
numeric matrix of BAF values |
hom.cutoff |
numeric, values above this cutoff to be made NA (considered HOM) |
calls |
matrix of NA, CT, AG, etc. genotypes to select HETs (in normals). Dimnames must match baf matrix. |
call.pairs |
list, names represent target samples for HOMs to set to NA. Values represent columns in "calls" matrix. |
numeric matix of mBAF values
data(genoset,package="genoset") mbaf = baf2mbaf( genoset.ds[, , "baf"], hom.cutoff=0.9 ) calls = matrix(sample(c("AT","AA","CG","GC","AT","GG"),(nrow(genoset.ds) * 2),replace=TRUE),ncol=2,dimnames=list(rownames(genoset.ds),c("K","L"))) mbaf = baf2mbaf( genoset.ds[, , "baf"], 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 genoset.ds[, ,"mbaf"] = baf2mbaf( genoset.ds[, , "baf"], hom.cutoff=0.9 ) # Put mbaf back into the BAFSet object as a new element