Add a Kit-Ligand dataset, and correct the genotyping function

R/genotype.R

@@ -178,8 +178,11 @@ genotyping = function(sequencing,sequencing.error,phetero) {
   probas = matrix(0.0,nrow = nrow(sequencing),
                   ncol = nrow(pnucs))
   
+  
+  ACGT.cols = match(c('A','C','G','T'),names(sequencing))
+  
   for (i in seq_len(nrow(sequencing))) {
-      obs = as.numeric(sequencing[i,4:7])
+      obs = as.numeric(sequencing[i,ACGT.cols])
     for (j in seq_len(nrow(pnucs))) {
       theo= as.numeric(pnucs[j,1:4])
        probas[i,j] = dmultinomialACGT(obs[1],obs[2],obs[3],obs[4],
@@ -206,11 +209,13 @@ genotyping = function(sequencing,sequencing.error,phetero) {
   
   best.genotype   = apply(probas, MARGIN = 1, which.max)
   
-  
   second.genotype = apply(probas, MARGIN = 1, function(x) which(x==second(x))[1])
   
 
   g.good = rownames(pnucs)[best.genotype]
+  haplotype1 = substr(as.character(g.good),1,1)
+  haplotype2 = substr(as.character(g.good),2,2)
+  
   g.alt  = rownames(pnucs)[second.genotype]
 
   lod = apply(probas, MARGIN = 1, max)
@@ -218,7 +223,7 @@ genotyping = function(sequencing,sequencing.error,phetero) {
   
   true = apply(sequencing[,1:2],MARGIN = 1,function(x) paste0(sort(x),collapse = ""))
    
-  sequencing = cbind(sequencing,probas,g.good,g.alt,lod,score = exp(score),ok=true==g.good)
+  sequencing = cbind(sequencing,probas,g.good,haplotype1,haplotype2,g.alt,lod,score = exp(score),ok=true==g.good)
   
   return(sequencing)
 }

RawData/prepare_data.R

+kitlg.gene = read.table("RawData/ROO-D6-5104.3_124450000-124600000.bases.txt",
+                   header=FALSE)
+
+names(kitlg.gene)=c("position","A","C","G","T")
+usethis::use_data(kitlg.gene,overwrite = TRUE)