Parallel genehunter: implementation of a linkage analysis package for distributed-memory architectures

  • Authors:

  • Gavin C. Conant;Steven J. Plimpton;William Old;Andreas Wagner;Pamela R. Fain;Theresa R. Pacheco;Grant Heffelfinger

  • Affiliations:

  • Department of Biology, 167 Castetter Hall, The University of New Mexico, Albuquerque, NM;Computation, Computers, and Mathematics Center, Sandia National Laboratories, Albuquerque, NM;Agilent Laboratories, Fort Collins, CO;Department of Biology, 167 Castetter Hall, The University of New Mexico, Albuquerque, NM;Health Sciences Center, The University of Colorado, Fort Collins, CO;Health Sciences Center, The University of Colorado, Fort Collins, CO;Computation, Computers, and Mathematics Center, Sandia National Laboratories, Albuquerque, NM

  • Venue:
  • Journal of Parallel and Distributed Computing - High-performance computational biology
  • Year:
  • 2003

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Abstract

We present a parallel algorithm for performing multipoint linkage analysis of genetic marker data on large family pedigrees. The algorithm effectively distributes both the computation and memory requirements of the analysis. We discuss an implementation of the algorithm in the Genehunter linkage analysis package (version 2.1), enabling Genehunter to run on distributed-memory platforms for the first time. Our preliminary benchmarks indicate reasonable scalability of the algorithm even for fixed-size problems, with parallel efficiencies of 75% or more on up to 128 processors. In addition, we have extended the hard-coded limit of 16 non-founding individuals in Genehunter 2.1 to a new limit of 32 non-founding individuals.