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ABC framework based on the distribution of segregationg sites between populations and Random Forest to perform model choice

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ABC-FDSS: ABC framework using random forest coupled with the FDSS or SFS

FDSS stands for Frequency Distribution of Segregating Sites. Briefly, it records the number of genomic loci of a fixed length showing a certain number of segregatin sites across individuals (from 0 (monomorphic) to a fixed maximum number n)

The main compute_sfs.py script can:

  • Compute the FDSS within and between populations
  • Compute the unfolded/folded site frequency spectrum within and between populations
  • Compute the number of differences between chr within and between populations using SNPs simulated with Hudson's ms.

Arguments:

-h, --help show this help message and exit

-np NPOP, --nrpop NPOP Number of populations

-nc NCHR, --nrchr NCHR Vector containing the number of chr for each pop (es: 2,2,2 for a 3 population comparison)

-w LLW, --within LLW nr of categories that compose the whithin pop freq table (it has to be ajusted based on the expected within population polymorphism)

-b LLB, --between LLB nr of categories that compose the between pop freq table (it has to be ajusted based on the expected between population polymorphism)

-s, --segSitesPartition compute the private and the shared segregating sites between pairs of populations instead of pairwise differeces, with a minimum of two pops

-sfs, --siteFrequencySpectrum compute the 1D or 2D unfolded sfs instead of pairwise differeces

-folded, --folded fold the site frequency spectrum

-d, --debug print delimiters ("|") between pops and pairwise comparison only using -s

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ABC framework based on the distribution of segregationg sites between populations and Random Forest to perform model choice

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