Estimating and interpreting FST: The impact of rare variants

  1. Alkes L. Price2,4,5,7
  1. 1Harvard–Massachusetts Institute of Technology (MIT), Division of Health, Science, and Technology, Cambridge, Massachusetts 02139, USA;
  2. 2Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA;
  3. 3Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA;
  4. 4Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, USA;
  5. 5Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA
    1. 6 These authors contributed equally to this work.

    Abstract

    In a pair of seminal papers, Sewall Wright and Gustave Malécot introduced FST as a measure of structure in natural populations. In the decades that followed, a number of papers provided differing definitions, estimation methods, and interpretations beyond Wright's. While this diversity in methods has enabled many studies in genetics, it has also introduced confusion regarding how to estimate FST from available data. Considering this confusion, wide variation in published estimates of FST for pairs of HapMap populations is a cause for concern. These estimates changed—in some cases more than twofold—when comparing estimates from genotyping arrays to those from sequence data. Indeed, changes in FST from sequencing data might be expected due to population genetic factors affecting rare variants. While rare variants do influence the result, we show that this is largely through differences in estimation methods. Correcting for this yields estimates of FST that are much more concordant between sequence and genotype data. These differences relate to three specific issues: (1) estimating FST for a single SNP, (2) combining estimates of FST across multiple SNPs, and (3) selecting the set of SNPs used in the computation. Changes in each of these aspects of estimation may result in FST estimates that are highly divergent from one another. Here, we clarify these issues and propose solutions.

    Footnotes

    • 7 Corresponding authors

      E-mail gbhatia{at}mit.edu

      E-mail nickp{at}broadinstitute.org

      E-mail aprice{at}hsph.harvard.edu

    • [Supplemental material is available for this article.]

    • Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.154831.113.

    • Received January 11, 2013.
    • Accepted July 9, 2013.

    This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported), as described at http://creativecommons.org/licenses/by-nc/3.0/.

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