A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees
Author(s) -
Mark Silberstein,
Omer Weissbrod,
Lars Otten,
Anna Tzemach,
Andrei Anisenia,
Oren Shtark,
Dvir Tuberg,
Eddie Galfrin,
Irena Gan,
Adel Shalata,
Zvi Borochowitz,
Rina Dechter,
E. A. Thompson,
Dan Geiger
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts658
Subject(s) - tag snp , computer science , snp , markov chain monte carlo , workflow , linkage (software) , data mining , pedigree chart , theoretical computer science , haplotype , single nucleotide polymorphism , bayesian probability , genetics , artificial intelligence , database , biology , gene , genotype
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.
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