added individual masking

README.md

@@ -50,6 +50,17 @@ get masking region example for the population _Mus musculus musculus AFG_:
 ```
 INPUT=Mmm_AFG.combined.bga
 OUTPUT=Mmm_AFG.combined.bga.stcov5
+
+awk '{if($4<5) print $0}' $INPUT > $INPUT".stcov5"
+bedtools merge -i $INPUT".stcov5" > $INPUT".stcov5.merge"
+awk -v OFS='\t' '{print $1,$2,$3,4}' $INPUT".stcov5.merge" > $OUTPUT
+```
+
+get masking region example for individual 396 of the population _Mus musculus musculus AFG_:
+```
+INPUT=AFG1_396.bam.bga
+OUTPUT=AFG1_396.bam.bga.stcov5
+
 awk '{if($4<5) print $0}' $INPUT > $INPUT".stcov5"
 bedtools merge -i $INPUT".stcov5" > $INPUT".stcov5.merge"
 awk -v OFS='\t' '{print $1,$2,$3,4}' $INPUT".stcov5.merge" > $OUTPUT
@@ -121,13 +132,13 @@ echo $INPUT4".mpileup.q0Q10.vcf.gz" >> $MPILEUPLIST
 echo $INPUT5".mpileup.q0Q10.vcf.gz" >> $MPILEUPLIST
 echo $INPUT6".mpileup.q0Q10.vcf.gz" >> $MPILEUPLIST
 
-MPILEUPOUTPUT=AFG.mpileup.q0Q10.vcf.gz
+MPILEUPOUTPUT=Mmm_AFG.mpileup.q0Q10.vcf.gz
 
 bcftools merge -m all -O z -o $MPILEUPOUTPUT -l $MPILEUPLIST
 
 #call SNP and INDEL
 
-OUTPUT=AFG.mpileup.q0Q10.bcfcall.mv.vcf.gz
+OUTPUT=Mmm_AFG.mpileup.q0Q10.bcfcall.mv.vcf.gz
 
 bcftools call -O z -f GQ -m -v -o $OUTPUT $MPILEUPOUTPUT
 ```
@@ -143,13 +154,118 @@ _used software:_
 
 ### Get population specific SNPs
 
+To get population specific CONSENSUS VCF files the VCF file produced with 'bcftools call' was first re-coded into population specific VCF files with 'vcftools'. Further the population specific VCF file containing multiple individuals was parsed with 'vcfparser.py mvcf2consensus' to obtain a CONSENSUS VCF file for each population. This CONSENSUS VCF files were used to generate pseudo-genomes files per natural population with 'vcfparser.py vcf2fasta' using also the masking regions (see "Get masking regions for individual samples and natural populations").
+
+vcftools example for the population _Mus musculus musculus AFG_:
+```
+#example for population Mmm_AFG:
+#
+#VCF IDs:
+#
+#396
+#413
+#416
+#424
+#435
+#444
+
+POPIDS=AFG.vcf.ids
+
+echo "396" >> $POPIDS
+echo "413" >> $POPIDS 
+echo "416" >> $POPIDS
+echo "424" >> $POPIDS
+echo "435" >> $POPIDS
+echo "444" >> $POPIDS
+
+GZVCF=Mmm_AFG.mpileup.q0Q10.bcfcall.mv.vcf.gz
+OUTPUT=Mmm_AFG.mpileup.q0Q10.bcfcall.mv.remIndels
+
+vcftools --gzvcf $GZVCF --remove-indels --recode --recode-INFO-all --non-ref-ac-any 1 --keep $POPIDS --out $OUTPUT
+```
+
+vcfparser.py mvcf2consensus example for the population _Mus musculus musculus AFG_:
+```
+#example for population Mmm_AFG:
+#
+#VCF IDs:
+#
+#396
+#413
+#416
+#424
+#435
+#444
+
+INPUT=Mmm_AFG.mpileup.q0Q10.bcfcall.mv.remIndels.recode.vcf
+OUTPUT=Mmm_AFG.mpileup.q0Q10.bcfcall.mv.remIndels.recode.consensus
+
+python vcfparser.py mvcf2consensus -ivcf $INPUT -o $OUTPUT -cdp 11 -chr chr1,chr2,chr3,chr4,chr5,chr6,chr7,chr8,chr9,chr10,chr11,chr12,chr13,chr14,chr15,chr16,chr17,chr18,chr19,chrX,chrY -samples 396,413,416,424,435,444 -id Mmm_AFG.mv
+```
+
+vcfparser.py vcf2fasta example for the population _Mus musculus musculus AFG_:
+```
+#example for population Mmm_AFG:
+#
+
+REFERENCE=mm10.fasta
+INPUT=Mmm_AFG.mpileup.q0Q10.bcfcall.mv.remIndels.recode.consensus.vcf
+OUTPUT=Mmm_AFG.mpileup.q0Q10.chr1.bcfcall.mv.remIndels.recode.consensus.chr
+MASKFILE=Mmm_AFG.combined.bga.stcov5
+
+python vcfparser.py vcf2fasta -ivcf $INPUT -o $OUTPUT -R $REFERENCE -samples Mmm_AFG.mv -chr chr1,chr2,chr3,chr4,chr5,chr6,chr7,chr8,chr9,chr10,chr11,chr12,chr13,chr14,chr15,chr16,chr17,chr18,chr19,chrX,chrY -ibga $MASKFILE -cov2N 4
+```
+
+_used software:_
+
++ vcftools v0.1.15
++ vcfparser.py <https://gitlab.gwdg.de/evolgen/introgression/blob/master/scripts/vcfparser.py>
+
+### Calculate K80 distance between populations using the CONSENSUS pseudo-genome files
+
+## Nucleotide diversity calculations
+
+### Get individual specific SNPs
+
+To get individual specific VCF files the VCF file produced with 'bcftools call' was first re-coded for each individual with 'vcftools'. Further the individual specific VCF files were used to generate pseudo-genomes files per individual with 'vcfparser.py vcf2fasta' using individual masking regions (see "Get masking regions for individual samples and natural populations").
+
+vcftools example for individual 396 of the population _Mus musculus musculus AFG_:
+```
+#example for individual 396 of the population Mmm_AFG:
+#
+#VCF IDs:
+#
+#396
+
+GZVCF=Mmm_AFG.mpileup.q0Q10.bcfcall.mv.vcf.gz
+OUTPUT=Mmm_AFG1.396.mpileup.q0Q10.bcfcall.mv.remIndels
+
+vcftools --gzvcf $GZVCF --remove-indels --recode --recode-INFO-all --non-ref-ac-any 1 --indv 396 --out $OUTPUT
+```
+
+vcfparser.py vcf2fasta example for individual 396 of the population _Mus musculus musculus AFG_:
+```
+#example for individual 396 of the population Mmm_AFG:
+#
+
+REFERENCE=mm10.fasta
+INPUT=Mmm_AFG1.396.mpileup.q0Q10.bcfcall.mv.remIndels.recode.consensus.vcf
+OUTPUT=Mmm_AFG1.396.mpileup.q0Q10.chr1.bcfcall.mv.remIndels.recode.consensus.chr
+MASKFILE=Mmm_AFG.combined.bga.stcov5
+
+python vcfparser.py vcf2fasta -ivcf $INPUT -o $OUTPUT -R $REFERENCE -samples Mmm_AFG.mv -chr chr1,chr2,chr3,chr4,chr5,chr6,chr7,chr8,chr9,chr10,chr11,chr12,chr13,chr14,chr15,chr16,chr17,chr18,chr19,chrX,chrY -ibga $MASKFILE -cov2N 4
+```
+
 _used software:_
 
-### Calculate population specific Consensus sequence
++ vcftools v0.1.15
++ vcfparser.py <https://gitlab.gwdg.de/evolgen/introgression/blob/master/scripts/vcfparser.py>
+
+### Calculate nucleotide diversity within each population
 
 _used software:_
 
-### Calculate K80 distance between populations
++ variscan v2.0.3
 
 ## Dxy distance calculation
 
@@ -161,3 +277,6 @@ _used software:_
 
 _used software:_
 
+## Simulation
+
+