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Bioinformatics. 2015 Nov 15;31(22):3709-11. doi: 10.1093/bioinformatics/btv449. Epub 2015 Jul 29.

SNPGenie: estimating evolutionary parameters to detect natural selection using pooled next-generation sequencing data.

Author information

1
Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA and.
2
Department of Pathobiological Sciences, University of Wisconsin School of Veterinary Medicine, Madison, WI 53706, USA.

Abstract

New applications of next-generation sequencing technologies use pools of DNA from multiple individuals to estimate population genetic parameters. However, no publicly available tools exist to analyse single-nucleotide polymorphism (SNP) calling results directly for evolutionary parameters important in detecting natural selection, including nucleotide diversity and gene diversity. We have developed SNPGenie to fill this gap. The user submits a FASTA reference sequence(s), a Gene Transfer Format (.GTF) file with CDS information and a SNP report(s) in an increasing selection of formats. The program estimates nucleotide diversity, distance from the reference and gene diversity. Sites are flagged for multiple overlapping reading frames, and are categorized by polymorphism type: nonsynonymous, synonymous, or ambiguous. The results allow single nucleotide, single codon, sliding window, whole gene and whole genome/population analyses that aid in the detection of positive and purifying natural selection in the source population.

AVAILABILITY AND IMPLEMENTATION:

SNPGenie version 1.2 is a Perl program with no additional dependencies. It is free, open-source, and available for download at https://github.com/hugheslab/snpgenie.

CONTACT:

nelsoncw@email.sc.edu or austin@biol.sc.edu

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
26227143
PMCID:
PMC4757956
DOI:
10.1093/bioinformatics/btv449
[Indexed for MEDLINE]
Free PMC Article

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