Merge pull request #4 from cchu70/master

remove weird blank characters

Author: julianhess

src/get_CN_Absolute.Phylogic_SinglePatientTiming.R

@@ -5,43 +5,43 @@ option.list <- list(
 	make_option("--pair_id", dest="pair_id"),
 	make_option("--abs_lib_dir", dest="abs_lib_dir"),
 	make_option("--pcawg", dest="pcawg", default="FALSE"))
-​
+
 opt <- parse_args(OptionParser(option_list=option.list))
 print(opt)
-​
+
 Called_Absolute= opt[["Called_Absoute"]]
 CGA_DIR_ABS= opt[["abs_lib_dir"]]
 pair_id= opt[["pair_id"]]
 PCAWG= opt[["pcawg"]]
-​
+
 Out_Name=file.path(paste(pair_id,"tsv",sep="."))
-​
+
 print( paste("sourcing files in ", CGA_DIR_ABS, sep=""))
-​
+
 rr = dir(CGA_DIR_ABS,full.names=TRUE )
 for( i in 1:length(rr) ) {
   source(rr[i])}
 load(Called_Absolute)
 input_purity=seg.obj$mode.res$mode.tab[[1]]
-​
+
 allele.segs= get_hom_pairs_segtab(seg.obj)
-​
+
 ExtractSampleObs <<- AllelicExtractSampleObs
 GetCopyRatioComb <<- AllelicGetCopyRatioComb
 SCNA_model = seg.obj[["mode.res"]][["mode_SCNA_models"]][[1]] 
 tree_clust = resort_tree_clusters( SCNA_model, SCNA_model[["seg_CCF_DP"]][["tree_clust"]] )
-​
+
 SCNA_model[["seg_CCF_DP"]][["tree_clust"]] = tree_clust
 SCNA_model[["seg_CCF_DP"]][["seg_clust_tab"]] = get_seg_clust_tab( SCNA_model )
 mut_cols = SCNA_model[["seg_CCF_DP"]][["tree_clust"]][["assign"]]
-​
+
 mode.tab <- seg.obj[["mode.res"]][["mode.tab"]]
-​
+
 res = get_b_and_delta( mode.tab[1, "alpha"], mode.tab[1, "tau"] )
 delta = res$delta
 b = res$b
 segs_d0 = deconstruct_SCNAs( SCNA_model, seg.obj, allele.segs, b, delta )
-​
+
 AS.seg.ix = allele.segs[, c("seg.ix.1", "seg.ix.2")]
 d0.allele.segs = allele.segs
 d0.allele.segs[,"A1.Seg.CN"] =segs_d0[ AS.seg.ix[,1] ]
@@ -52,34 +52,34 @@ d0.allele.segs["seg.ix.2"] = NULL
 d0.allele.segs["W"] = NULL
 d0.allele.segs=rename(d0.allele.segs, c("Start.bp"="Start", 
 "End.bp"="End","n_probes"="N_probes","length"="Length","A1.Seg.sem"="A1.Sigma","A2.Seg.sem"="A2.Sigma")) 
-​
+
 write.table(d0.allele.segs, file = Out_Name, append = FALSE, quote = FALSE, sep = "\t",
             eol = "\n", na = "NA", dec = ".", row.names = FALSE,
             col.names = TRUE)
 if(PCAWG=="TRUE"){
 Out_Name=file.path(paste(pair_id,"segments.txt",sep="_"))
 load(Called_Absolute)
 input_purity=seg.obj$mode.res$mode.tab[[1]]
-​
+
   ExtractSampleObs <<- AllelicExtractSampleObs
   GetCopyRatioComb <<- AllelicGetCopyRatioComb
   SCNA_model = seg.obj[["mode.res"]][["mode_SCNA_models"]][[1]]
   tree_clust = resort_tree_clusters( SCNA_model, SCNA_model[["seg_CCF_DP"]][["tree_clust"]] )
-​
+
   SCNA_model[["seg_CCF_DP"]][["tree_clust"]] = tree_clust
   SCNA_model[["seg_CCF_DP"]][["seg_clust_tab"]] = get_seg_clust_tab( SCNA_model )
   mut_cols = SCNA_model[["seg_CCF_DP"]][["tree_clust"]][["assign"]]
-​
+
   mode.tab <- seg.obj[["mode.res"]][["mode.tab"]]
-​
+
   res = get_b_and_delta( mode.tab[1, "alpha"], mode.tab[1, "tau"] )
   delta = res$delta
   b = res$b
   segs_d0 = deconstruct_SCNAs( SCNA_model, seg.obj, allele.segs, b, delta )
-​
-​
+
+
   sc_tab = seg.obj[["mode.res"]][["subclonal_SCNA_res"]][["subclonal_SCNA_tab"]][1,,]
-​
+
   nc = ncol(SCNA_model[["collapsed_CCF_dens"]])
   GRID = cumsum( c(0, rep(1/(nc-1),(nc-1))))
   clust_dens = SCNA_model[["seg_CCF_DP"]][["tree_clust"]][["CCF_dens"]]
@@ -88,53 +88,49 @@ input_purity=seg.obj$mode.res$mode.tab[[1]]
   #clust_dens_str = paste(as.character(one), collapse=", ")
   ccf_hats=max.col(clust_dens)/100
   mut_cols = SCNA_model[["seg_CCF_DP"]][["tree_clust"]][["assign"]]
-​
+
   sc_ix=mut_cols != which(clust_dens[,1]==1)
   sc_ix[is.na(sc_ix) & sc_tab[,"subclonal_ix"]==0]=0
   sc_ix[sc_ix==FALSE]=0
   sc_ix[sc_ix==TRUE]=1
-​
+
   #sc_ix_noNA=sc_ix
   #sc_ix_noNA[is.na(sc_ix)]=-1
   #segs_d0[sc_ix_noNA==0]=round(segs_d0[sc_ix_noNA==0])
-​
+
   AS.seg.ix = allele.segs[, c("seg.ix.1", "seg.ix.2")]
   d0.allele.segs = allele.segs
   d0.allele.segs[,"A1.Seg.CN"] = round(segs_d0[ AS.seg.ix[,1] ])
   d0.allele.segs[,"A2.Seg.CN"] = round(segs_d0[ AS.seg.ix[,2] ])
-​
+
   d0.allele.segs["W"] = NULL
   d0.allele.segs=rename(d0.allele.segs, c("Start.bp"="Start", 
 "End.bp"="End","n_probes"="N_probes","length"="Length","A1.Seg.sem"="A1.Sigma","A2.Seg.sem"="A2.Sigma"))
-​
+
   d0.allele.segs["seg.ix.1"] = NULL
   d0.allele.segs["seg.ix.2"] = NULL
   d0.allele.segs["A1.Sigma"] = NULL
   d0.allele.segs["A2.Sigma"] = NULL
-​
-​
-​
+
   A1.Subclonal.ix = sc_ix[AS.seg.ix[,1]]
   A2.Subclonal.ix = sc_ix[AS.seg.ix[,2]]
   A1.Subclonal.CN = sc_tab[,"qs"][AS.seg.ix[,1]]
   A2.Subclonal.CN = sc_tab[,"qs"][AS.seg.ix[,2]]
   A1.Clonal.CN = sc_tab[,"qc"][AS.seg.ix[,1]]
   A2.Clonal.CN = sc_tab[,"qc"][AS.seg.ix[,2]]
-​
-​
-​
+
   A1.CCF_hat = ccf_hats[mut_cols[AS.seg.ix[,1]]]
   A2.CCF_hat = ccf_hats[mut_cols[AS.seg.ix[,2]]]
   A1.CCF_dens = clust_dens_str[mut_cols[AS.seg.ix[,1]]]
   A2.CCF_dens = clust_dens_str[mut_cols[AS.seg.ix[,2]]]
-​
-​
+
+
   A1.CCF_hat[is.na(A1.CCF_hat)]=sc_tab[,"CCF_hat"][AS.seg.ix[,1]][is.na(A1.CCF_hat)]
   A2.CCF_hat[is.na(A2.CCF_hat)]=sc_tab[,"CCF_hat"][AS.seg.ix[,2]][is.na(A2.CCF_hat)]
-​
+
   d0.allele.segs[,"CCF"]=1
   d0.allele.segs[,"CCF_dens"]=clonal_clust_dens_str
-​
+
   clonal.ix=intersect(which(A1.Subclonal.ix == 0),which(A2.Subclonal.ix == 0))
   a1.sub.ix=intersect(which(A1.Subclonal.ix != 0),which(A2.Subclonal.ix == 0))
   a2.sub.ix=intersect(which(A1.Subclonal.ix == 0),which(A2.Subclonal.ix != 0))
@@ -143,49 +139,49 @@ input_purity=seg.obj$mode.res$mode.tab[[1]]
   A1_Sub_Clonal_Seg=d0.allele.segs[intersect(which(A1.Subclonal.ix != 0),which(A2.Subclonal.ix == 0)),]
   A2_Sub_Clonal_Seg=d0.allele.segs[intersect(which(A1.Subclonal.ix == 0),which(A2.Subclonal.ix != 0)),]
   Both_Sub_Clonal_Seg=d0.allele.segs[intersect(which(A1.Subclonal.ix != 0),which(A2.Subclonal.ix != 0)),]
-​
-​
+
+
   d0.allele.segs[,"Historically.Clonal"]=0
-​
+
   if (length(a1.sub.ix) > 0){
     d0.allele.segs[a1.sub.ix,"A1.Seg.CN"]=A1.Clonal.CN[a1.sub.ix]
     d0.allele.segs[a1.sub.ix,"CCF"]=1#-A1.CCF_hat[a1.sub.ix]
     d0.allele.segs[a1.sub.ix,"CCF_dens"]=clonal_clust_dens_str
     d0.allele.segs[a1.sub.ix,"Historically.Clonal"]=1
-​
-​
+
+
     a1_segs=d0.allele.segs[a1.sub.ix,]
     a1_segs["A1.Seg.CN"]=A1.Subclonal.CN[a1.sub.ix]
     a1_segs["CCF"]=A1.CCF_hat[a1.sub.ix]
     a1_segs["CCF_dens"]=A1.CCF_dens[a1.sub.ix]
     a1_segs["Historically.Clonal"]=0
-​
+
   }else{
   a1_segs=NULL}
   if (length(a2.sub.ix) > 0){
     d0.allele.segs[a2.sub.ix,"A2.Seg.CN"]=A2.Clonal.CN[a2.sub.ix]
     d0.allele.segs[a2.sub.ix,"CCF"]=1#-A2.CCF_hat[a2.sub.ix]
     d0.allele.segs[a2.sub.ix,"CCF_dens"]=clonal_clust_dens_str
     d0.allele.segs[a2.sub.ix,"Historically.Clonal"]=1
-​
+
     a2_segs=d0.allele.segs[a2.sub.ix,]
     a2_segs["A2.Seg.CN"]=A2.Subclonal.CN[a2.sub.ix]
     a2_segs["CCF"]=A2.CCF_hat[a2.sub.ix]
     a2_segs["CCF_dens"]=A2.CCF_dens[a2.sub.ix]
     a2_segs["Historically.Clonal"]=0
   }else{
-​
+
   a2_segs=NULL}
   if (length(all.sub.ix) > 0){
-​
+
     d0.allele.segs[all.sub.ix,"A1.Seg.CN"]=A1.Clonal.CN[all.sub.ix]
     d0.allele.segs[all.sub.ix,"A2.Seg.CN"]=A2.Clonal.CN[all.sub.ix]
     matched= A1.CCF_hat[all.sub.ix] == A2.CCF_hat[all.sub.ix]
-​
+
     d0.allele.segs[all.sub.ix[!matched],"CCF"]=1#-A1.CCF_hat[all.sub.ix[!matched]]-A2.CCF_hat[all.sub.ix[!matched]]
     d0.allele.segs[all.sub.ix[!matched],"CCF_dens"]=clonal_clust_dens_str
     d0.allele.segs[all.sub.ix[!matched],"Historically.Clonal"]=1
-​
+
     d0.allele.segs[all.sub.ix[matched],"CCF"]=1#-A1.CCF_hat[all.sub.ix[matched]]
     d0.allele.segs[all.sub.ix[matched],"CCF_dens"]=clonal_clust_dens_str
     d0.allele.segs[all.sub.ix[matched],"Historically.Clonal"]=1
@@ -195,17 +191,17 @@ input_purity=seg.obj$mode.res$mode.tab[[1]]
       all_sub_a1_segs["CCF"]=A1.CCF_hat[all.sub.ix[!matched]]
       all_sub_a1_segs["CCF_dens"]=A1.CCF_dens[all.sub.ix[!matched]]
       all_sub_a1_segs["Historically.Clonal"]=0
-​
+
       all_sub_a2_segs=d0.allele.segs[all.sub.ix[!matched],]
       all_sub_a2_segs["A2.Seg.CN"]=A2.Subclonal.CN[all.sub.ix[!matched]]
       all_sub_a2_segs["CCF"]=A2.CCF_hat[all.sub.ix[!matched]]
       all_sub_a2_segs["CCF_dens"]=A2.CCF_dens[all.sub.ix[!matched]]
       all_sub_a2_segs["Historically.Clonal"]=0
     }else{
-​
+
       all_sub_a1_segs=NULL
       all_sub_a2_segs=NULL
-​
+
     }
     if (length(all.sub.ix[matched])> 0){
       euqal_sub_seg=d0.allele.segs[all.sub.ix[matched],]
@@ -214,30 +210,30 @@ input_purity=seg.obj$mode.res$mode.tab[[1]]
       euqal_sub_seg["CCF"]=A1.CCF_hat[all.sub.ix[matched]]
       euqal_sub_seg["CCF_dens"]=A1.CCF_dens[all.sub.ix[matched]]
       euqal_sub_seg["Historically.Clonal"]=0
-​
+
     }else{
-​
+
     euqal_sub_seg=NULL}}
-​
+
   else{
-​
+
     all_sub_a1_segs=NULL
     all_sub_a2_segs=NULL
     euqal_sub_seg=NULL
   }   
-​
+
 comb_segtab=rbind(d0.allele.segs,a1_segs,a2_segs,all_sub_a1_segs,all_sub_a2_segs,euqal_sub_seg)
-​
+
 comb_segtab=comb_segtab[with(comb_segtab, order(as.integer(comb_segtab[["Chromosome"]]), as.integer(comb_segtab[["Start"]]))), ]
-​
+
 comb_segtab[,"copy_number"]=comb_segtab[["A1.Seg.CN"]]+comb_segtab[["A2.Seg.CN"]]
 comb_segtab["N_probes"]=NULL
 comb_segtab["Length"]=NULL
-​
+
 comb_segtab=rename(comb_segtab, c("Chromosome"="chromosome","Start"="start", 
 "End"="end","A1.Seg.CN"="minor_cn","A2.Seg.CN"="major_cn","CCF"="ccf","Historically.Clonal"="historically_clonal")) 
 comb_segtab=comb_segtab[,c(1,2,3,9,4,5,6,8)]
-​
+
 write.table(comb_segtab, file = Out_Name, append = FALSE, quote = FALSE, sep = "\t",
             eol = "\n", na = "NA", dec = ".", row.names = FALSE,
             col.names = TRUE)