diff --git a/R/calc.hrd.R b/R/calc.hrd.R
index 7571bf3..5f91f24 100644
--- a/R/calc.hrd.R
+++ b/R/calc.hrd.R
@@ -4,7 +4,7 @@
 #' @param nA column number of copy number of A allele
 #' @param sizelimit lower limit of the size of LOHs
 #' @return number of LOH
-calc.hrd<-function(seg, nA=7, return.loc=FALSE,sizelimit1){
+calc.hrd<-function(seg, nA=6, return.loc=FALSE,sizelimit1){
   nB <- nA+1
   output <- rep(0, length(unique(seg[,1])))
   names(output) <- unique(seg[,1])
@@ -40,4 +40,3 @@ calc.hrd<-function(seg, nA=7, return.loc=FALSE,sizelimit1){
     return(output)
   }
 }
-
diff --git a/R/calc.lst.R b/R/calc.lst.R
index 51e5426..ce840d4 100644
--- a/R/calc.lst.R
+++ b/R/calc.lst.R
@@ -5,7 +5,7 @@
 #' @param nA column number of copy number of A allele
 #' @param chr.arm option to use chromosome arms defined during segmentation
 #' @return number of LSTs
-calc.lst<-function(seg, chrominfo=chrominfo,nA=7,chr.arm='no'){
+calc.lst<-function(seg, chrominfo=chrominfo,nA=6,chr.arm='no'){
   nB <- nA+1
   samples <- unique(seg[,1])
   output <- setNames(rep(0,length(samples)), samples)
diff --git a/R/scar_score.R b/R/scar_score.R
index 5a1fa38..285ef98 100644
--- a/R/scar_score.R
+++ b/R/scar_score.R
@@ -43,19 +43,19 @@ scar_score<-function(seg,reference = "grch38", seqz=FALSE, ploidy=NULL, sizelimi
   res_ai<- calc.ai_new(seg = seg, chrominfo = chrominfo) #<-- the first column is what I need
   #Calculating the large scale transition scores:
   res_lst <- calc.lst(seg = seg, chrominfo = chrominfo) #<-- You need to use the chrominfo.snp6 file! Nicolai sent it to you!
-  sum_HRD0<-res_lst+res_hrd+res_ai[1]
+  sum_HRD0<-res_lst+res_hrd+res_ai[,1]
 
   if (is.null(ploidy)){
     sum_HRDc<-NA
   } else {
-    sum_HRDc<-res_lst-15.5*ploidy+res_hrd+res_ai[1]
+    sum_HRDc<-res_lst-15.5*ploidy+res_hrd+res_ai[,1]
   }
 
-  #HRDresulst<-c(res_hrd,res_ai,res_lst,sum_HRD0,sum_HRDc)
+  #HRDresulst<-cbind(res_hrd,res_ai[,1],res_lst,sum_HRD0,sum_HRDc)
   #names(HRDresulst)<-c("HRD",colnames(res_ai),"LST", "HRD-sum","adjusted-HRDsum")
-  HRDresulst<-c(res_hrd,res_ai[1],res_lst,sum_HRD0)
-  names(HRDresulst)<-c("HRD",colnames(res_ai)[1],"LST", "HRD-sum")
-  run_name<-names(sum_HRD0)
-  write.table(t(HRDresulst),paste0(outputdir,"/",run_name,"_HRDresults.txt"),col.names=NA,sep="\t",row.names=unique(seg[,1]))
+  HRDresulst<-cbind(res_hrd,res_ai[,1],res_lst,sum_HRD0)
+  colnames(HRDresulst)<-c("HRD",colnames(res_ai)[1],"LST", "HRD-sum")
+  assign("HRDresulst",as.data.frame(HRDresulst),envir = .GlobalEnv)
+  write.table(t(HRDresulst),paste0(outputdir,"/","HRDresults.txt"),sep="\t")
   return(t(HRDresulst))
 }