grenedalf: population genetic statistics for the next generation of pool sequencing

Author:

Czech Lucas12ORCID,Spence Jeffrey P3ORCID,Expósito-Alonso Moisés14567ORCID

Affiliation:

1. Department of Plant Biology, Carnegie Institution for Science , Stanford, CA 94305, United States

2. Section for GeoGenetics, Globe Institute, University of Copenhagen , 1350 København, Denmark

3. Department of Genetics, Stanford University , Stanford, CA 94305, United States

4. Department of Biology, Stanford University , Stanford, CA 94305, United States

5. Department of Global Ecology, Carnegie Institution for Science , Stanford, CA 94305, United States

6. Department of Integrative Biology, University of California Berkeley , Berkeley, CA 94720, United States

7. Howard Hughes Medical Institute, University of California Berkeley , Berkeley, CA 94720, United States

Abstract

Abstract Summary Pool sequencing is an efficient method for capturing genome-wide allele frequencies from multiple individuals, with broad applications such as studying adaptation in Evolve-and-Resequence experiments, monitoring of genetic diversity in wild populations, and genotype-to-phenotype mapping. Here, we present grenedalf, a command line tool written in C++ that implements common population genetic statistics such as θ, Tajima’s D, and FST for Pool sequencing. It is orders of magnitude faster than current tools, and is focused on providing usability and scalability, while also offering a plethora of input file formats and convenience options. Availability and implementation grenedalf is published under the GPL-3, and freely available at github.com/lczech/grenedalf.

Funder

Carnegie Institution for Science

National Institutes of Health’s Early Investigator

University of California Berkeley, and the Howard Hughes Medical Institute

Publisher

Oxford University Press (OUP)

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