Haplotype matching in large cohorts using the Li and Stephens model

Bioinformatics
Gerton Lunter

Abstract

The Li and Stephens model, which approximates the coalescent describing the pattern of variation in a population, underpins a range of key tools and results in genetics. Although highly efficient compared to the coalescent, standard implementations of this model still cannot deal with the very large reference cohorts that are starting to become available, and practical implementations use heuristics to achieve reasonable runtimes. Here I describe a new, exact algorithm ('fastLS') that implements the Li and Stephens model and achieves runtimes independent of the size of the reference cohort. Key to achieving this runtime is the use of the Burrows-Wheeler transform, allowing the algorithm to efficiently identify partial haplotype matches across a cohort. I show that the proposed data structure is very similar to, and generalizes, Durbin's positional Burrows-Wheeler transform.

References

Apr 1, 1983·Theoretical Population Biology·R R Hudson
Oct 29, 2005·Nature·UNKNOWN International HapMap Consortium
Jun 8, 2007·Nature·UNKNOWN Wellcome Trust Case Control Consortium
Mar 6, 2009·Genome Biology·Ben LangmeadSteven L Salzberg
May 20, 2009·Bioinformatics·Heng Li, Richard Durbin

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Citations

Sep 4, 2019·Nature Genetics·Jerome KelleherGil McVean
Feb 15, 2020·Algorithms for Molecular Biology : AMB·Jarno AlankoJens Stoye
Feb 25, 2021·Bioinformatics·Ahsan SanaullahShaojie Zhang

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Software Mentioned

scrm

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