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19. Inference of Population Splits
George Pacheco edited this page Aug 4, 2021
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1 revision
Based on
Dataset III
, we perform an Inference of Population Splits.
cat ~/data/Pigeons/PBGP/PBGP--Analyses/Lists/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals--Article--Ultra.labels | awk '{split($0,a,"_"); print $1"\t"a[1]}' > ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals--Article--Ultra.annot
perl $SCRIPTS/scripts/geno2treemix.pl --geno ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--ANGSDRuns/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.geno.gz --format angsd --skip_cols 4 --pop ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals--Article--Ultra.annot | gzip --best > ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.treemix.gz
for M in `seq 6 8`
do
echo $SCRIPTS/scripts/wrapper_treemix.sh -i ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.treemix.gz -k 100 -t 10 -noss -m $M -root Crupestris -global -o ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.treemix.${M}
done | xsbatch -c 10 --mem-per-cpu 1024 -J TreeMix -R --max-array-jobs 11 --time 10-00 --
zcat ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.treemix.gz | head -n 1 | perl -p -e 's/ /\n/g' > ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.treemix.poporder
ls -Sv ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.treemix.XXX.llik | perl -p -e 's/\.llik//g' | Rscript --vanilla --slave -e "source('$SOFT/treemix/v1.13/src/plotting_funcs.R'); h=18; w=h*2; x<-read.table('stdin')[,1]; pdf(height=h,width=w); layout(matrix(c(1,2),ncol=2),c(w/2,w/2),c(h)); for(i in x){plot_tree(i);plot_resid(i,'~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.treemix.poporder')}; dev.off()"; mv Rplots.pdf ~/data/Pigeons/PBGP/PBGP--Analyses/PBGP--TreeMix/PBGP--GoodSamples_WithWGSs_NoOddSamplesNoFerals_SNPCalling--Article--Ultra.treemix.XXX.pdf
- 1. Data Access
- 2. Sequencing Quality Check
- 3. Demultiplexing
- 4. Creation of Mapping Targets
- 5. Filtering For Chimeric Reads
- 6. GBS Sexing
- 7. Read Processing & Mapping
- 8. Running Stats & Filtering of Bad Samples
- 9. Filtering of Possible Paralogs
- 10. Merging of Duplicate Cases
- 11. Investigation of Filtering of Possible Paralogs
- 12. Creation of Specific Datasets
- 13. Loci Information
- 14. Heterozygosity Calculation
- 15. Population Genetics Statistics
- 16. Phylogenetic Reconstruction
- 17. Multidimensional Scaling
- 18. Estimation of Individual Ancestries
- 19. Inference of Population Splits
- 20. Measuring of Linkage Disequilibrium
- 21. GWAS