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Rapid haplotype inference for nuclear families

Amy L Williams1*, David E Housman2, Martin C Rinard1 and David K Gifford1

Author Affiliations

1 Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar Street, Cambridge, MA, 02139, USA

2 David H. Koch Institute for Integrative Cancer Research at MIT, Massachusetts Institute of Technology, 40 Ames Street, Cambridge, MA, 02142, USA

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Genome Biology 2010, 11:R108  doi:10.1186/gb-2010-11-10-r108

Published: 29 October 2010

Abstract

Hapi is a new dynamic programming algorithm that ignores uninformative states and state transitions in order to efficiently compute minimum-recombinant and maximum likelihood haplotypes. When applied to a dataset containing 103 families, Hapi performs 3.8 and 320 times faster than state-of-the-art algorithms. Because Hapi infers both minimum-recombinant and maximum likelihood haplotypes and applies to related individuals, the haplotypes it infers are highly accurate over extended genomic distances.