In order to investigate the possibility of linked selection influencing the ratio of insertions to deletions (rDI) in regions of low recombination, INDELs where binned into a number of 50Kb windows according to gene distance.
$ mkdir distance_bin_beds_2kb_from_cds/
$ zcat /fastdata/bop15hjb/GT_ref/gt_noncoding.bed.gz | ./create_gene_proximity_bins.py -bin_size 2000 -max_dist 100000 -out_prefix distance_bin_beds_2kb_from_cds/gt_noncoding_cds_proximity_2kbwindows
$ ls distance_bin_beds_2kb_from_cds/*bed.gz | python check_bin_population.py > distance_bin_beds_2kb_from_cds/bin_summaries_2kb_nc.txt
$ ls distance_bin_beds_2kb_from_cds/*bed.gz > distance_bin_beds_2kb_from_cds/2kb_bed_list.txt
$ ./proximity_anavar.py -vcf /fastdata/bop15hjb/GT_data/BGI_BWA_GATK/Analysis_ready_data/final/bgi_10birds.filtered_indels.pol.anno.recomb.line.vcf.gz -bed_list distance_bin_beds_2kb_from_cds/2kb_bed_list.txt -call_fa /fastdata/bop15hjb/GT_ref/bgi_10birds.callable.fa -dfe continuous -out_pre /fastdata/bop15hjb/GT_data/BGI_BWA_GATK/anavar_analysis/anavar_cds_distance_2kb_nc/gt_sel_ar_ref_cdsdist_2kb -sub -evolgen
$ ls /fastdata/bop15hjb/GT_data/BGI_BWA_GATK/anavar_analysis/anavar_cds_distance_2kb_nc/*results* | ../anavar_analyses/process_anavar_results.py -file_pattern bin,_bin\(\\d+-\?\\d\*\)\\. | cut -f 1-18 -d ',' > gt_nc_v_ar_2kb_wind_cds.results.csv
$ Rscript window_plots.R gt_nc_v_ar_2kb_wind_cds.results.csv 2kb_nc_cds_dist.png 2000
| x (x vs distance) | Spearman's rho | p-value |
|---|---|---|
| ins_theta | 0.2842257 | 0.04581 |
| del_theta | 0.4741897 | 0.0005822 |
| rdi | 0.08052821 | 0.5772 |
We also assessed how much of this was from neutral variation and how much deleterious.
python linked_dfe.py -res_csv gt_nc_v_ar_2kb_wind_cds.results.csv > nc_dfe_exon_dist.txt
Rscript exon_dist_dfe.RResults: theta plot, proportion plot
mkdir distance_bin_beds_2kb_from_cds_withsfs/
ls $PWD/distance_bin_beds_2kb_from_cds/*gz | while read i; do ls $i | cut -d '.' -f 2 | tr '\n' '\t'; echo $i; done > 2kb_binids_beds.txt
../summary_analyses/automate_bed_summary.py -indel_vcf /fastdata/bop15hjb/h_j_b/GT_data/BGI_BWA_GATK/Analysis_ready_data/final/bgi_10birds.filtered_indels.pol.anno.recomb.line.vcf.gz -snp_vcf /fastdata/bop15hjb/h_j_b/GT_data/BGI_BWA_GATK/Analysis_ready_data/final/bgi_10birds.filtered_snps.pol.anno.degen.line.vcf.gz -region_list 2kb_binids_beds.txt -out_pre distance_bin_beds_2kb_from_cds/gt_prox_summary_raw -evolgen
../summary_analyses/automate_bed_summary.py -indel_vcf /fastdata/bop15hjb/h_j_b/GT_data/BGI_BWA_GATK/Analysis_ready_data/final/bgi_10birds.filtered_indels.pol.anno.recomb.line.vcf.gz -snp_vcf /fastdata/bop15hjb/h_j_b/GT_data/BGI_BWA_GATK/Analysis_ready_data/final/bgi_10birds.filtered_snps.pol.anno.degen.line.vcf.gz -region_list 2kb_binids_beds.txt -correct_sfs -out_pre distance_bin_beds_2kb_from_cds_withsfs/gt_prox_summary -evolgen
../summary_analyses/automate_bed_callable.py -call_fa /fastdata/bop15hjb/GT_ref/bgi_10birds.callable.fa -chr_list /fastdata/bop15hjb/GT_ref/gt_autosomes.txt -region_list 2kb_binids_beds.txt -out_pre distance_bin_beds_2kb_from_cds_withsfs/gt_prox_call
cd distance_bin_beds_2kb_from_cds_withsfs/
head -n 1 gt_prox_summary_bin1_stats.txt > gt_prox_summary_stats.txt
cat gt_prox_summary_bin*_stats.txt | grep -v cat | sort -n -k1.4 >> gt_prox_summary_stats.txt
cp gt_prox_summary_stats.txt ../
head -n 1 gt_prox_call_bin1.txt > gt_prox_call.txt
cat gt_prox_call*.txt | grep -v cat | sort -n -k1.4 >> gt_prox_call.txt
cp gt_prox_call.txt ../
cd distance_bin_beds_2kb_from_cds/
head -n 1 gt_prox_summary_raw_bin1_stats.txt > gt_prox_summary_stats_raw.txt
cat gt_prox_summary_raw_bin*_stats.txt | grep -v cat | sort -n -k1.4 >> gt_prox_summary_stats_raw.txt
cp gt_prox_summary_stats_raw.txt ../
cd ..
Rscript window_plots_sum_stats.R
| x (x vs distance) | Spearman's rho | p-value |
|---|---|---|
| ins_theta | 0.8410564 | 2.2e-16 |
| del_theta | 0.7878511 | 2.2e-16 |
Rscript correlation_power.R Plot here.