cisEffectTune {sigaR} | R Documentation |
Decides which test to perform: loss vs. no-loss (tumor surpressor) or no-gain vs gain (proto-onco). Followed by a tuning algorithm that enhances the overal power of the FDR procedure by excluding genes with either unbalanced (many samples having a high call probability of, say, a loss) or imprecise (many call probabilities close to 0.5) soft calls, which is likely to increase the probability of detection for genes with a more favorable call probability distribution.
cisEffectTune(CNdata, GEdata, testStatistic, nGenes=250, nPerm=250, minCallProbMass=0.10, verbose=TRUE)
CNdata |
Object of class |
GEdata |
Object of class |
testStatistic |
Test statistic to be used, either |
nGenes |
Number of genes used for tuning. |
nPerm |
Number of permutation used for tuning. |
minCallProbMass |
A number inbetween 0 and 1. Genes with a marginal call probabilities in one of the classes smaller than |
verbose |
Boolean to suppress output, either |
A numeric
-object with the genes selected for testing. Numbering corresponds to genes of the pre-tuned, but matched data set.
This function is a rewritten version of the intCNGEan.tune
function of the intCNGEan
-package.
Wessel N. van Wieringen: w.vanwieringen@vumc.nl
Van Wieringen, W.N., Van de Wiel, M.A. (2009), "Non-parametric testing for DNA copy number induced differential mRNA gene expression", Biometrics, 65(1), 19-29.
matchAnn2Ann
, cisEffectTest
# load data data(pollackCN16) data(pollackGE16) # select genes that are likely to have a significant genomic cis-effect on expression levels genes2test <- cisEffectTune(pollackCN16, pollackGE16, "wmw", nGenes=50, nPerm=50)