Pool-hmm: a Python program for estimating the allele frequency spectrum and detecting selective sweeps from next generation sequencing of pooled samples

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Abstract

Due to its cost effectiveness, next generation sequencing of pools of individuals (Pool-Seq) is becoming a popular strategy for genome-wide estimation of allele frequencies in population samples. As the allele frequency spectrum provides information about past episodes of selection, Pool-seq is also a promising design for genomic scans for selection. However, no software tool has yet been developed for selection scans based on Pool-Seq data. We introduce Pool-hmm, a Python program for the estimation of allele frequencies and the detection of selective sweeps in a Pool-Seq sample. Pool-hmm includes several options that allow a flexible analysis of Pool-Seq data, and can be run in parallel on several processors. Source code and documentation for Pool-hmm is freely available at https://qgsp.jouy.inra.fr/.

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Most cited references 8

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Genomic scans for selective sweeps using SNP data.

Rasmus Nielsen, Scott Williamson, Yuseob Kim … (2005)

Detecting selective sweeps from genomic SNP data is complicated by the intricate ascertainment schemes used to discover SNPs, and by the confounding influence of the underlying complex demographics and varying mutation and recombination rates. Current methods for detecting selective sweeps have little or no robustness to the demographic assumptions and varying recombination rates, and provide no method for correcting for ascertainment biases. Here, we present several new tests aimed at detecting selective sweeps from genomic SNP data. Using extensive simulations, we show that a new parametric test, based on composite likelihood, has a high power to detect selective sweeps and is surprisingly robust to assumptions regarding recombination rates and demography (i.e., has low Type I error). Our new test also provides estimates of the location of the selective sweep(s) and the magnitude of the selection coefficient. To illustrate the method, we apply our approach to data from the Seattle SNP project and to Chromosome 2 data from the HapMap project. In Chromosome 2, the most extreme signal is found in the lactase gene, which previously has been shown to be undergoing positive selection. Evidence for selective sweeps is also found in many other regions, including genes known to be associated with disease risk such as DPP10 and COL4A3.

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The next generation of molecular markers from massively parallel sequencing of pooled DNA samples.

Andreas Futschik, Christian Schlötterer (2010)

Next generation sequencing (NGS) is about to revolutionize genetic analysis. Currently NGS techniques are mainly used to sequence individual genomes. Due to the high sequence coverage required, the costs for population-scale analyses are still too high to allow an extension to nonmodel organisms. Here, we show that NGS of pools of individuals is often more effective in SNP discovery and provides more accurate allele frequency estimates, even when taking sequencing errors into account. We modify the population genetic estimators Tajima's π and Watterson's to obtain unbiased estimates from NGS pooling data. Given the same sequencing effort, the resulting estimators often show a better performance than those obtained from individual sequencing. Although our analysis also shows that NGS of pools of individuals will not be preferable under all circumstances, it provides a cost-effective approach to estimate allele frequencies on a genome-wide scale.

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OmegaPlus: a scalable tool for rapid detection of selective sweeps in whole-genome datasets.

Katherine Stamatakis, N Alachiotis, Stelios P Pavlidis (2012)

Recent advances in sequencing technologies have led to the rapid accumulation of molecular sequence data. Analyzing whole-genome data (as obtained from next-generation sequencers) from intra-species samples allows to detect signatures of positive selection along the genome and therefore identify potentially advantageous genes in the course of the evolution of a population. We introduce OmegaPlus, an open-source tool for rapid detection of selective sweeps in whole-genome data based on linkage disequilibrium. The tool is up to two orders of magnitude faster than existing programs for this purpose and also exhibits up to two orders of magnitude smaller memory requirements. OmegaPlus is available under GNU GPL at http://www.exelixis-lab.org/software.html.

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Author and article information

Journal

Journal ID (nlm-ta): Mol Ecol Resour

Journal ID (iso-abbrev): Mol Ecol Resour

Journal ID (publisher-id): men

Title: Molecular Ecology Resources

Publisher: Blackwell Publishing Ltd

ISSN (Print): 1755-098X

ISSN (Electronic): 1755-0998

Publication date (Print): March 2013

Publication date (Electronic): 11 January 2013

Volume: 13

Issue: 2

Pages: 337-340

Affiliations

[1 ]Laboratoire de Génétique Cellulaire, INRA 24 Chemin de Borde Rouge, Auzeville CS 52627, Castanet Tolosan Cedex, 31326, France

[2 ]Institut für Populationsgenetik, Vetmeduni Vienna Veterinärplatz 1, Wien, A-1210, Austria

[3 ]Institute of Statistics and Operations Research, University of Vienna Universitätsstrasse 5/9, Wien, A-1010, Austria

Author notes

Correspondence: Simon Boitard, Fax: +33 561285308; E-mail: simon.boitard@ 123456toulouse.inra.fr

Article

DOI: 10.1111/1755-0998.12063

PMC ID: 3592992

PubMed ID: 23311589

SO-VID: 6c5478a0-7aa0-4af9-8a71-d82ffc0198e2

License:

Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.

History

Date received : 10 July 2012

Date revision received : 26 November 2012

Date accepted : 29 November 2012

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