./data/baseline/:
- stg.G30.meanDP15.mac3.G70.l50.ID.vcf: vcf file after filtering (328 individuals, 55,112 SNPs) with ID column.
- stg.G30.meanDP15.mac3.G70.l50.id: list of snp IDs in the filtered vcf file.
- popmap_sturgeon_N328.txt: popmap for 328 individuals after filtering.
./data/panel_development/
- sumstats_acrosspops.csv: summary statistics for 55,112 SNPs, generated using polyfreqs output files.
- N502_primer.csv: primer information of 502 loci in the final optimized GTseq panel.
- GTseq_sturgeon_primer_probe_final502.txt: primer/probe file for the final GTseq panel with 502 loci.
- primer_great.csv: primer information of 206 loci with 258 great SNPs.
./data/gtseq/:
- sturgeon_sampleinfo_updated.csv: sample meta information for 936 samples used in GTseq.
- parentage.csv: raw parentage relationship information (unconfirmed).
- true_parentage.txt: true parent-offspring trio relationship (confirmed).
- minAF01_AvgReadDepth200_429loci_773SNPs_AlleleRatioCategory.list: a list of 773 informative SNPs with good coverage (average read depth >=200, AF>=1%) along with their allele ratio categories (great, okay, tbd).
/scatterPlots_429loci_773SNPs/: allele ratio plots by three categories (great, okay, tbd).- polyGenResults_singSNP_letter_good.txt: GTscore/polyGen genotype output (4N).
- polygene input files:
- polygene_geno_pop_input.txt: input for 180 samples for population analysis (all 773 SNPs).
- polygene_geno_pop_greatLoci.txt: input for 180 samples for population structure analysis (258 great SNPs only).
- polygene_trio_geno_input.txt: input for 177 samples used for parentage analysis (all 773 SNPs).
- polygene output files:
- o_parentage_paternity.txt: output for likelihood-based paternity analysis;
- o_relatedness_edited.txt: output for pairwise relatedness analysis.
The following scripts are for reference only. Please adjust accordingly for your computing environment and working directory.
./scripts/:
- AlleleCount_vcf_4n.py: python script to generate input matrices to run polyfreqs for a ploidy of 4N. Adopted from the original AlleleCount.py from Limborg, Larson, Seeb, & Seeb (2017).
- polyfreqs_parallel.r & polyfreqs_parallel.slurm: run polyfreqs for all pops in parallel.
- polyfreqs_postrun.rmd: process polyfreqs output files and generate summary statistics.
- MI_calculation.r & MI_plot.r: analyses of Mendelian incompatibilities.
- paternity_LODplot.r: likelihood-based paternity plot.
- relatedness.r: pairwise relatedness analysis.