Ancestry_Amel.yml : YAML file to create the conda enviroment required to run the following analyses. Example of how to create and activate conda enviroment: conda env create -f Ancestry_Amel.yml conda activate Ancestry_Amel

Directory PR: Contains the sample and panel files used to run Ancstry_HMM and AHMM-S on the Puerto Rican population of Africanized honey bee. The marginals are the population average of the Ancestry_HMM results. The ahmms-forw files are the AHMMS results for selection on African ancestry. The ahmms-rev files are the AHMMS results for selection on European ancestry.

Directory MA: Contains the sample and panel files used to run Ancstry_HMM and AHMM-S on the Mesoamerican population of Africanized honey bee. The marginals are the population average of the Ancestry_HMM results. The ahmms-forw files are the AHMMS results for selection on African ancestry. The ahmms-rev files are the AHMMS results for selection on European ancestry.

Directory GO_Enrichment : Contains our implentation of GO Enrichement Analyses. Given an panel file, relvant annotations, and number of identified peaks, it will randomly sample peaks from AIMs in non-overlapping genomic regions, consistent with our peak filtering criteria, 10 million times to produce GO term distributions for each ancestry-specific selection scenario.

Directory VariantCalling: VCFs generated using GATK 4.2.5 or later require sites that are no-calls to be formatted as "." instead of the reference allele in the genotype field. This can be done using the following bcftools command: bcftools +setGT example.vcf.gz -- -t q -n . -i 'FMT/DP=0'

Pythong scripts used to generate GATK variant calling pipeline.

Directoy pi : Examples of how to calculate nucleotide divesitry around AIMs using angsd.

Directory lai : Running ancestry HMM and AHHM-S

Example of how to generate PANEL files using vcf2aHMM.py : python vcf2aHMM.py --vcf chr1.vcf --dist 2500 --pop ahmm.pop --distM 1e-4 --map apis.map -geno --minGTP 25 --minGTA 0.8 --minDif 0.10 1>chr1.panel 2>chr1.err

Example of how to run Ancestry_HMM : ancestry_hmm -i chr1.panel -s PR.sample -e 1e-3 --ne 100000 -g -a 2 0.5 0.5 -p 0 10000 0.5 -p 1 -100 0.5 1>chr1.out 2>chr1.err

Example of how to run AHMM-S : ahmm-s -i chr1.panel -g -s PR.sample -p 1 10000 0.5 -p 0 100 0.5 --window p 100 --gss 2 980000 1 0.001 0.5 --ne 100000 1>ahmms-forw-chr1.out 2>ahmms-forw-chr1.err

runAHMM.sh is an example of how to run this interatively.

peakFinder.py can simply be run after specifying the populations, directions, and location of the data.