title: A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees.
abstract: BACKGROUND
  The use of dense single nucleotide polymorphism (SNP) data in genetic linkage analysis of large pedigrees is impeded by significant technical, methodological and computational challenges. Here we describe Superlink-Online SNP, a new powerful online system that streamlines the linkage analysis of SNP data. It features a fully integrated flexible processing workflow comprising both well-known and novel data analysis tools, including SNP clustering, erroneous data filtering, exact and approximate LOD calculations and maximum-likelihood haplotyping. The system draws its power from thousands of CPUs, performing data analysis tasks orders of magnitude faster than a single computer. By providing an intuitive interface to sophisticated state-of-the-art analysis tools coupled with high computing capacity, Superlink-Online SNP helps geneticists unleash the potential of SNP data for detecting disease genes.
  
  
  RESULTS
  Computations performed by Superlink-Online SNP are automatically parallelized using novel paradigms, and executed on unlimited number of private or public CPUs. One novel service is large-scale approximate Markov Chain-Monte Carlo (MCMC) analysis. The accuracy of the results is reliably estimated by running the same computation on multiple CPUs and evaluating the Gelman-Rubin Score to set aside unreliable results. Another service within the workflow is a novel parallelized exact algorithm for inferring maximum-likelihood haplotyping. The reported system enables genetic analyses that were previously infeasible. We demonstrate the system capabilities through a study of a large complex pedigree affected with metabolic syndrome.
  
  
  BACKGROUND
  Superlink-Online SNP is freely available for researchers at http://cbl-hap.cs.technion.ac.il/superlink-snp. The system source code can also be downloaded from the system website.
  
  
  BACKGROUND
  omerw@cs.technion.ac.il
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.
authors.forename: Mark
authors.initials: M
authors.lastname: Silberstein
authors.forename: Omer
authors.initials: O
authors.lastname: Weissbrod
authors.forename: Lars
authors.initials: L
authors.lastname: Otten
authors.forename: Anna
authors.initials: A
authors.lastname: Tzemach
authors.forename: Andrei
authors.initials: A
authors.lastname: Anisenia
authors.forename: Oren
authors.initials: O
authors.lastname: Shtark
authors.forename: Dvir
authors.initials: D
authors.lastname: Tuberg
authors.forename: Eddie
authors.initials: E
authors.lastname: Galfrin
authors.forename: Irena
authors.initials: I
authors.lastname: Gannon
authors.forename: Adel
authors.initials: A
authors.lastname: Shalata
authors.forename: Zvi U
authors.initials: ZU
authors.lastname: Borochowitz
authors.forename: Rina
authors.initials: R
authors.lastname: Dechter
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Thompson
authors.forename: Dan
authors.initials: D
authors.lastname: Geiger
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D008040:Genetic Linkage; D006239:Haplotypes; D006801:Humans; D008390:Markov Chains; D009010:Monte Carlo Method; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide; D012984:Software