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Bioinformatics. 2018 Sep 15;34(18):3205-3207. doi: 10.1093/bioinformatics/bty299.

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

Author information

1
Institute for Computer Science and Department of Biology, Heinrich Heine University, Düsseldorf, Germany.
2
Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.
3
Cluster of Excellence on Plant Sciences, Düsseldorf, Germany.

Abstract

Summary:

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.

Availability and implementation:

The R implementation of our method, which builds on the powerful population genetics and genomics software PopGenome, is available freely from CRAN.

Supplementary information:

Supplementary data are available at Bioinformatics online.

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