Parsing genomic data

The module includes functions to parse TGP from Uricchio et al. (2019) and DGN from Murga-Moreno et al. (2019). In addition, the module have a function to parse SFS and divergence from multi-FASTA data following Murga-Moreno et al. (2019)

Please to parse raw data into SFS and divergence counts, first download raw files deposited in our repository:

• TGP
• DGN Zambia population
• DGN Raleigh population

mkdir -p analysis/
curl -o analysis/tgp.txt https://raw.githubusercontent.com/jmurga/Analytical.jl/master/data/tgp.txt
curl -o analysis/dgnRal.txt https://raw.githubusercontent.com/jmurga/Analytical.jl/master/data/dgnRal.txt

Parsing TGP and DGN data manually

Once you have downloaded the files, you can use the function Analytical.parse_sfs to convert the data into SFS and divergence counts. Please check Analytical.parse_sfs to get more info o execute:

alpha, sfs, divergence = Analytical.parse_sfs(sample_size = 661, data = "analysis/tgp.txt")

To save the data, you can use CSV and DataFrames packages

using CSV, DataFrames
CSV.write("analysis/tgp_sfs.tsv",DataFrame(sfs,:auto),delim='\t',header=false)
CSV.write("analysis/tgp_div.tsv",DataFrame(permutedims(divergence),:auto),delim='\t',header=false)

It is possible to directly subset genes IDs using Ensembl or Flybase id. Use a variable of type Matrix{String} into the argument geneList

download('https://raw.githubusercontent.com/jmurga/Analytical.jl/master/data/ensembl_list.txt','analysis/ensembl_list.txt')
ensembl_list = CSV.read("analysis/ensembl_list.txt",header=false,DataFrame) |> Array

alpha, sfs, divergence = Analytical.parse_sfs(sample_size = 661, data = "analysis/tgp.txt",gene_list = ensembl_list)

If you are going to parse DGN, you need to change the value of the argument isoline to true. Following the Murga-Moreno et al. (2019) sample size for each population is:

• Zambia population: 154
• RAL population: 160

alpha, sfs, divergence = Analytical.parse_sfs(sample_size = 160, data = "analysis/dgn_ral.txt",isolines=true)