BlockFeST: Bayesian calculation of region-specific FST to detect local adaptation

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Abstract

The fixation index FST can be used to identify non-neutrally evolving loci from genome-scale SNP data across two or more populations. Recent years have seen the development of sophisticated approaches to estimate FST based on Markov-Chain Monte-Carlo simulations. Here, we present a vectorized R implementation of an extension of the widely used BayeScan software for codominant markers, adding the option to group individual SNPs into pre-defined blocks. A typical application of this new approach is the identification of genomic regions, genes, or gene sets containing SNPs that evolved under directional selection.

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Pfeifer, B., & Lercher, M. J. (2018). BlockFeST: Bayesian calculation of region-specific FST to detect local adaptation. Bioinformatics, 34(18), 3205–3207. https://doi.org/10.1093/bioinformatics/bty299

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