Computational Haplotype Inference from Pooled Samples

Methods Mol Biol. 2017:1551:309-319. doi: 10.1007/978-1-4939-6750-6_15.

Abstract

Computationally inferring the identities and their relative frequencies from pooled samples that are whole-genome or segmentally genotyped or sequenced (e.g., using next-generation sequencing) in a pool is useful for population genetics analysis. To carry out such analysis, one needs to understand basics of how to use high-performance computing (HPC) facilities and the specifics of corresponding computational tools. Here, we describe the basic knowledge and step-by-step usage of a number of tools for haplotype inference on genotyping or next-generation sequencing data.

Keywords: Bioinformatics; Computing cluster; Genotyping; Haplotype; Next-generation sequencing.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Genotype
  • Haplotypes / genetics
  • Humans
  • Polymorphism, Single Nucleotide / genetics