| dichotomizeCN {integIRTy} | R Documentation |
Dichotomizing copy number data based on segmented data (i.e. log2ratio).
Description
A simple dichotomization procedure is implemented for CN data that only requires two cutoffs.
Usage
dichotomizeCN(CN, CNctr = NULL, tau1 = -0.3, tau2 = 0.3)
Arguments
CN |
A matrix of gene wise copy number data for tumor samples. Rows are the genes; columns are the samples. |
CNctr |
A matrix of copy number data for normal samples. The program first guess if this is paired data by comparing if tumor and normal sample has equal sample size. If TRUE, then normal samples will be subtracted element by element to correct for germline CN change. Otherwise, no correction is performed. The program proceeds with only tumor data. |
tau1 |
The lower bound for log2Ratio when converting to a code as 0. |
tau2 |
The upper bound for log2Ratio when converting to a code as 0. Log2ratio between tau1 and tau2 is converted to 0 and 1 otherwise. |
Value
Returns a binary matrix of the same dimension. Missing value would be propogated into the binary matrix.
Author(s)
Pan Tong (nickytong@gmail.com), Kevin R Coombes (krc@silicovore.com)
References
Tong P, Coombes KR. integIRTy: a method to identify altered genes in cancer accounting for multiple mechanisms of regulation using item response theory. Bioinformatics, 2012 Nov 15; 28(22):2861–9.
See Also
dichotomizeExpr, dichotomizeMethy
Examples
data(OV)
binDat <- dichotomizeCN(CN_T[1:20, ], CN_N[1:20, ])
binDat[15:20, 1:2]