z-logo
Premium
Pool‐hmm: a Python program for estimating the allele frequency spectrum and detecting selective sweeps from next generation sequencing of pooled samples
Author(s) -
Boitard Simon,
Kofler Robert,
Françoise Pierre,
Robelin David,
Schlötterer Christian,
Futschik Andreas
Publication year - 2013
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/1755-0998.12063
Subject(s) - python (programming language) , allele frequency , hidden markov model , computer science , selection (genetic algorithm) , software , source code , documentation , population , allele , biology , artificial intelligence , genetics , programming language , gene , demography , sociology
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/.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom