`rosettaPvalue` <- function( readsA, sigmaA=rosettaSigma(readsA), normFacA=1,
readsB, sigmaB=rosettaSigma(readsB), normFacB=1,
nBasesInGene=1000) {
# based on the Rosetta error model by John Castle
# turn the raw values into normalized, by length of gene and total reads
geneFactor <- 1000 / nBasesInGene
facA <- geneFactor * normFacA
normCntA <- readsA * facA
facB <- geneFactor * normFacB
normCntB <- readsB * facB
difInten <- normCntA - normCntB
sumSigma <- sqrt( ((sigmaA*facA)^2) + ((sigmaB*facB)^2))
xdev <- difInten / sumSigma
Pvalue <- erfc( abs( xdev) / sqrt(2))
return( Pvalue)
}
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