Estimating the ancestral recombinations graph (ARG) as compatible networks of SNP patterns

Laxmi Parida, Marta Melé, Francesc Calafell, Jaume Bertranpetit, Theodore G. Schurr, Fabrício R. Santos, Lluis Quintana-Murci, David Comas, Chris Tyler-Smith, Pierre A. Zalloua, Elena Balanovska, Oleg Balanovsky, Doron M. Behar, R. John Mitchell, Li Jin, Himla Soodyall, Ramasamy Pitchappan, Alan Cooper, Ajay K. Royyuru, Saharon RossetJason Blue-Smith, David F. Soria Hernanz, R. Spencer Wells

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Traditionally nonrecombinant genome, i.e., mtDNA or Y chromosome, has been used for phylogeography, notably for ease of analysis. The topology of the phylogeny structure in this case is an acyclic graph, which is often a tree, is easy to comprehend and is somewhat easy to infer. However, recombination is an undeniable genetic fact for most part of the genome. Driven by the need for a more complete analysis, we address the problem of estimating the ancestral recombination graph (ARG) from a collection of extant sequences. We exploit the coherence that is observed in the human haplotypes as patterns and present a network model of patterns to reconstruct the ARG. We test our model on simulations that closely mimic the observed haplotypes and observe promising results.

Original languageBritish English
Pages (from-to)1133-1154
Number of pages22
JournalJournal of Computational Biology
Volume15
Issue number9
DOIs
StatePublished - 1 Nov 2008

Keywords

  • ARG
  • Gene clusters
  • Genomic rearrangements
  • Recombinations
  • Strings

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