Nothing
calcBetas <- function(ped,betas){
# calculate odds ratios for each individual based on genotype data, given an odds ratio file
if (any(sapply(betas$rsID,function(x) length(grep(x,dimnames(ped)[[2]]))) == 0)){
stop("Not all SNPs in the odds ratio file are present in the ped file.")
}
# calculate count matrix
out1 <- t((t(ped[,5 + 2*(1:((length(ped[1,])-6)/2))]) == (betas$RiskAllele)) + (t(ped[,6 + 2*(1:((length(ped[1,])-6)/2))]) == (betas$RiskAllele)))
# find missing genotypes
missing <- (ped[,5 + 2*(1:((length(ped[1,])-6)/2))] == "N") + (ped[,5 + 2*(1:((length(ped[1,])-6)/2))] == "0") + (ped[,6 + 2*(1:((length(ped[1,])-6)/2))] == "N") + (ped[,6 + 2*(1:((length(ped[1,])-6)/2))] == "0")
out1[missing] <- NA
# perform prediction
prediction <- as.numeric(((betas$beta %*% t(out1)) - sum(betas$betaBar)))
# name the risk vector, and set missing indiviudals to missing
names(prediction) <- dimnames(ped)[[1]]
totMissing <- apply(ped[,7:length(ped[1,])],1,function(x) all(x == "0" | x == "N"))
prediction[totMissing] <- NA
class(prediction) <- "MangroveContPreds"
return(prediction)
}
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