Pedigree reconstruction using identity by descent

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-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 article 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 article 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
Pages (from-to)1481-1493
Number of pages13
JournalJournal of Computational Biology
Volume18
Issue number11
DOIs
StatePublished - 1 Nov 2011

Keywords

  • algorithms
  • combinatorial optimization
  • genetic analysis
  • genetic variation
  • machine learning

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