hapbin: An Efficient Program for performing Haplotype-Based Scans for Positive Selection in Large Genomic Datasets

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding how the genome is shaped by selective processes forms an integral part of modern biology. However, as genomic datasets continue to grow larger it is becoming increasingly difficult to apply traditional statistics for detecting signatures of selection to these cohorts. There is therefore a pressing need for the development of the next generation of computational and analytical tools for detecting signatures of selection in large genomic datasets. Here we present hapbin, an efficient multi-threaded implementation of extended haplotype homzygosity based statistics for detecting selection, which is up to 3,400 times faster than the current fastest implementations of these algorithms.
Original languageEnglish
Pages (from-to)3027-3029
Number of pages3
JournalMolecular Biology and Evolution
Volume32
Issue number11
Early online date6 Aug 2015
DOIs
Publication statusPublished - 1 Nov 2015

Keywords

  • selection
  • iHS
  • EHH
  • XP-EHH
  • Software

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