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c_score=function(mean_sig,var_sig,lambda='default'){
###########combining site level scores##############
com_stat=mean_sig
com_stat$mean_score=-qnorm(mean_sig$mean_p)####computing mean score####
com_stat=com_stat[order(com_stat$cpg),]
var_sig=var_sig[order(var_sig$cpg),]
var_p=var_sig$var_p
com_stat=cbind(com_stat,var_p)
com_stat$var_score=-qnorm(com_stat$var_p)####computing var score####3
com_stat$mean_score[which(com_stat$mean_score<=0)]=0
com_stat$var_score[which(com_stat$var_score<=0)]=0
com_stat$weight=com_stat[,4]+com_stat[,6]
com_stat=com_stat[which(com_stat$weight!=0),] ###delete cpg sites whose mean and var scores both smaller than 0#####
if (lambda=="default"){
com_stat$ratio=com_stat[,6]/(com_stat[,4]+com_stat[,6])###site level ration####
tapply(com_stat$ratio, com_stat$gene, function(x){return(mean(x))}) -> mean_lambda
data.frame(gene=names(mean_lambda), mean_lambda=mean_lambda) -> mean_lambda #####gene level ratio####3
com_stat=merge(com_stat,mean_lambda,by="gene")
lambda_default=unique(com_stat[,c(1,9)])
lambda_default=mean(lambda_default[,2]) ######computing lambda####
score=as.numeric(com_stat[,4])*lambda_default+as.numeric(com_stat[,6])*(1-lambda_default)
com_sig=cbind(com_stat[,c(1,2)],score) ####site level combined score####
} else if (lambda>=0 && lambda<=1){
score=as.numeric(com_stat[,4])*lambda+as.numeric(com_stat[,6])*(1-lambda)
com_sig=cbind(com_stat[,c(1,2)],score)
} else stop("Please input right lambda\n")
########computing gene leve score#########
tapply(com_sig$score, com_sig$gene, max) -> gene2weight
data.frame(gene=names(gene2weight), weight=gene2weight) -> gene2weight
gene2weight = gene2weight[!is.na(gene2weight[,2]), ]
return(gene2weight)
}
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