Pedigree Reconstruction Using Identity by Descent

Bonnie Kirkpatrick, Shuai Cheng Li, Richard M. Karp, Eran Halperin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Can we find the family trees, or pedigrees, that relate the haplotypes of a group of individuals? Collecting the genealogical information for how individuals are related is a very time-consuming and expensive process. Methods for automating the construction of pedigrees could stream-line this process. While constructing single-generation families is relatively easy given whole genome data, reconstructing multi-generational, possibly inbred, pedigrees is much more challenging. This paper addresses the important question of reconstructing monogamous, regular pedigrees, where pedigrees are regular when individuals mate only with other individuals at the same generation. This paper introduces two multi-generational pedigree reconstruction methods: one for inbreeding relationships and one for outbreeding relationships. In contrast to previous methods that focused on the independent estimation of relationship distances between every pair of typed individuals, here we present methods that aim at the reconstruction of the entire pedigree. We show that both our methods out-perform the state-of-the-art and that the outbreeding method is capable of reconstructing pedigrees at least six generations back in time with high accuracy. The two programs are available at http://cop.icsi.berkeley.edu/ cop.

Original languageEnglish
Title of host publicationResearch in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings
EditorsVineet Bafna, S. Cenk Sahinalp
PublisherSpringer Verlag
Pages136-152
Number of pages17
ISBN (Print)9783642200359
DOIs
StatePublished - 2011
Event15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011 - Vancouver, BC, Canada
Duration: 28 Mar 201131 Mar 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6577 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011
Country/TerritoryCanada
CityVancouver, BC
Period28/03/1131/03/11

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