Delete calc_SCC_for_RAD21_data.R

calc_SCC_for_RAD21_data.R

-library(hicrep)
-make_map <- function(B,chr_size,bin_size,ind_min)
-    {
-    data <- B
-    sz <- ceiling(chr_size/bin_size)
-    sq_mat <- matrix(0L, nrow = sz, ncol = sz)
-    for(i in 1 : dim(data)[1])
-        {
-        X1 <- data[i,2]
-        X2 <- data[i,5]
-        r_ind <- floor(X1/bin_size) - ind_min + 1
-        c_ind <- floor(X2/bin_size) - ind_min + 1
-
-        sq_mat[r_ind,c_ind] <- sq_mat[r_ind,c_ind] + data[i,7]
-        sq_mat[c_ind,r_ind] <-  sq_mat[c_ind,r_ind] + data[i,7]
-    }
-    return(sq_mat)
-}
-
-All <- NULL
-Po_DNN <- NULL
-Poe_DNN <- NULL
-seq1 <- seq(2,22,by=2)
-for(i in seq1)
-    {
-    if(i == 23)
-        {
-        C <- 'chrX'
-    }else{
-        C <- paste0('chr',i)
-    }
-    fname1 <- paste('/work/pathology/s206442/dbet_data/tables_SCC/Reduced_K562_',C,'_orig.bedpe',sep='')
-    Orig <- read.table(fname1,sep='\t',header=FALSE)
-    F <- paste0('/project/pathology/Mani_lab/s206442/K562_HiC/',C,'_RAD21_using_odd_training.csv')
-    P1 <- read.table(F,sep='\t',header=FALSE)
-    #P1[P1<0]<-0
-    Pred <- data.frame(Orig[,1:6],P1)
-    bin_size <- 25000
-    chr_size <- max(Orig[,6])
-    ind_min <- 0
-    sq_mat_orig <- make_map(Orig,chr_size,bin_size,ind_min)
-    sq_mat_pred <- make_map(Pred,chr_size,bin_size,ind_min)
-    scc.out <- get.scc(sq_mat_orig,sq_mat_pred, resol=25000,h=2,lbr=0, 1500000)
-    pred_scc <- scc.out$scc
-    print(pred_scc)
-    A1 <- as.vector(sq_mat_orig)
-    B1 <- as.vector(sq_mat_pred)
-    ind1 <- which(A1 != 0)
-    print(cor(A1[ind1],B1[ind1]))
-}