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Dsuite - fast D-statistics and related admixture evidence from VCF files

Citation

Malinsky, Milan; Matschiner, Michael; Svardal, Hannes (2020), Dsuite - fast D-statistics and related admixture evidence from VCF files, Dryad, Dataset, https://doi.org/10.5061/dryad.tdz08kpxt

Abstract

Patterson’s D, also known as the ABBA-BABA statistic, and related statistics such as the f4-ratio, are commonly used to assess evidence of gene flow between populations or closely related species. Currently available implementations often require custom file formats, implement only small subsets of the available statistics, and are impractical to evaluate all gene flow hypotheses across datasets with many populations or species due to computational inefficiencies. Here we present a new software package Dsuite, an efficient implementation allowing genome scale calculations of the D and f4-ratio statistics across all combinations of tens or hundreds of populations or species directly from a variant call format (VCF) file. Our program also implements statistics suited for application to genomic windows, providing evidence of whether introgression is confined to specific loci and it can also aid in interpretation of a system of f4-ratio results with the use of the ‘f-branch’ method. Dsuite is available at https://github.com/millanek/Dsuite, is straightforward to use, substantially more computationally efficient than comparable programs, and provides a convenient suite of tools and statistics, including some not previously available in any software package. Thus, Dsuite facilitates the assessment of evidence for gene flow, especially across larger genomic datasets.

Methods

This dataset includes the Malawi cichlid data and the simulated data used in the manuscript to evaluate performance of the Dsuite software and to illustrate the f-branch statistic. We also include a snapshot of the source code of the Dsuite package.

Funding

EMBO, Award: ALTF 456-2016

Norges Forskningsråd, Award: 275869

Swiss National Science Foundation, Award: 176039

Swiss National Science Foundation, Award: 176039