csmFinder <- function(candidate,data_type='regular',depth=10,distance=0.3,pval=0.05,thread=1){
if(data_type=='regular'){
model_result <- Nonparametric_Bayesian_clustering(candidate,delta= 0.5,tau = 0.5,nperm = 10000,thread=thread)
pCSM <- data.frame(candidate,t(model_result))
pCSM <- pCSM[which(pCSM$d>=distance & pCSM$pval<=pval),]
}else{
pCSM <- run.beta.mixture.model(candidate,thread=thread,cell_number=depth,adjusted_pval=pval,distance=distance)
}
}
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