title: SwiftLink: parallel MCMC linkage analysis using multicore CPU and GPU.
abstract: BACKGROUND
  Linkage analysis remains an important tool in elucidating the genetic component of disease and has become even more important with the advent of whole exome sequencing, enabling the user to focus on only those genomic regions co-segregating with Mendelian traits. Unfortunately, methods to perform multipoint linkage analysis scale poorly with either the number of markers or with the size of the pedigree. Large pedigrees with many markers can only be evaluated with Markov chain Monte Carlo (MCMC) methods that are slow to converge and, as no attempts have been made to exploit parallelism, massively underuse available processing power. Here, we describe SWIFTLINK, a novel application that performs MCMC linkage analysis by spreading the computational burden between multiple processor cores and a graphics processing unit (GPU) simultaneously. SWIFTLINK was designed around the concept of explicitly matching the characteristics of an algorithm with the underlying computer architecture to maximize performance.
  
  
  RESULTS
  We implement our approach using existing Gibbs samplers redesigned for parallel hardware. We applied SWIFTLINK to a real-world dataset, performing parametric multipoint linkage analysis on a highly consanguineous pedigree with EAST syndrome, containing 28 members, where a subset of individuals were genotyped with single nucleotide polymorphisms (SNPs). In our experiments with a four core CPU and GPU, SWIFTLINK achieves a 8.5× speed-up over the single-threaded version and a 109× speed-up over the popular linkage analysis program SIMWALK.
  
  
  BACKGROUND
  SWIFTLINK is available at https://github.com/ajm/swiftlink. All source code is licensed under GPLv3.
authors.affiliation: Division of Medicine, University College London, London WC1E 6BT, UK, Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland. alan.j.medlar@helsinki.fi
authors.forename: Alan
authors.initials: A
authors.lastname: Medlar
authors.forename: Dorota
authors.initials: D
authors.lastname: Głowacka
authors.forename: Horia
authors.initials: H
authors.lastname: Stanescu
authors.forename: Kevin
authors.initials: K
authors.lastname: Bryson
authors.forename: Robert
authors.initials: R
authors.lastname: Kleta
mesh_terms: D000465:Algorithms; D008040:Genetic Linkage; D023281:Genomics; D006319:Hearing Loss, Sensorineural / Q000235:genetics; D006801:Humans; D008607:Intellectual Disability / Q000235:genetics; D008390:Markov Chains; D009010:Monte Carlo Method; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide; D012640:Seizures / Q000235:genetics; D012984:Software