additional tools

SamueleSoraggi · Feb 25, 2021 · 03bd4d6 · 03bd4d6
1 parent ad6e3e6
commit 03bd4d6
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Showing 9 changed files with 10 additions and 5 deletions.
diff --git a/.gitignore b/.gitignore
@@ -3,3 +3,8 @@ __pycache__/
 # Ignore vim swap files
 *.swp
 *.swo
+._.DS_Store
+.DS_Store
+tools/nQuire.R~
+.gitignore
+simulMpileup.R~
diff --git a/Fitting_dist_contig.py b/Fitting_dist_contig.py
diff --git a/Genotype_Likelihoods.py b/Genotype_Likelihoods.py
diff --git a/HMMploidy.R b/HMMploidy.R
@@ -1268,8 +1268,8 @@ for(i in 1:length(fileVector)){ #loop over input files
         if(length(chrNameVar)>1){
             for(nn in chrNameVar){
                 ctgSites <- sitesSNP[chrSNP==nn]
-                print(nn)
-                print(ctgSites)
+                #print(nn)
+                #print(ctgSites)
                 if(!is.sorted(ctgSites))
                     stop( paste('The contig ', nn, ' contains unsorted values. This might be due by:\n',
                     '\t1) duplicated loci in your data ==> find and remove them\n',
@@ -1394,7 +1394,7 @@ for(i in 1:length(fileVector)){ #loop over input files
         p = .05
         mat2 <- mat
         print(mat)
-        if(length(mat)[1] > 1 & any(diag(mat)<p)){
+        if(length(mat)[1] > 1 & any(diag(mat)<p) & sum(diag(mat)<p)<dim(mat)[1]){
             for(l in 1:dim(mat)[1])
                 if(mat[l,l]>p)
                     keepIdx <- c(keepIdx,l)

diff --git a/LICENSE b/LICENSE
diff --git a/README.md b/README.md
diff --git a/generics.py b/generics.py
diff --git a/likelihoodDifference.R b/likelihoodDifference.R
diff --git a/simulMpileup.R b/simulMpileup.R
@@ -1,4 +1,4 @@
-# simulate mpileup file with different ploidy 1-5, assuming only 2 alleles and genotype frequencies defined by K and Ne and F
+# simulate mpileup file with different ploidy 1-6, assuming only 2 alleles and genotype frequencies defined by K and Ne and F
 
 # assume, population allele frequencies drawn from an exponential distribution
 
@@ -102,7 +102,7 @@ depth <- matrix( 0, nrow=nsams, ncol=nsites )
 for(samIdx in 1:nsams){
     rangeLams <- opt$depth * ncopy[samIdx] + (opt$depth * ncopy[samIdx] * opt$errdepth * c(-1,1))
     sampledLams <- runif(nsites, min=rangeLams[1], max=rangeLams[2])
-    depth[samIdx,] <- rpois(nsites,sampledLams)
+    depth[samIdx,] <- rpois(nsites,max(0.01,sampledLams)) #avoid negative or zero lambdas
     }
 
 rm(sampledLams)