Name
Title | ||
|---|---|---|
A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees. |
Abstract | ||
|---|---|---|
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.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.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.omerw@cs.technion.ac.ilSupplementary data are available at Bioinformatics online. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1093/bioinformatics/bts658 | Bioinformatics |
Keywords | DocType | Volume |
large pedigree,superlink-online snp,supplementary data,novel data analysis tool,erroneous data,snp clustering,snp data,approximate genetic linkage analysis,genetic linkage analysis,data analysis tasks order,maximum-likelihood haplotyping,genetic analysis,biomedical research,haplotypes,genetic linkage,cluster analysis,markov chains,algorithms,bioinformatics,monte carlo method | Journal | 29 |
Issue | ISSN | Citations |
2 | 1367-4811 | 1 |
PageRank | References | Authors |
0.37 | 24 | 14 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark Silberstein | 1 | 513 | 32.78 |
| Omer Weissbrod | 2 | 1 | 1.73 |
| Lars Otten | 3 | 83 | 8.06 |
| Anna Tzemach | 4 | 1 | 0.37 |
| Andrei Anisenia | 5 | 1 | 0.37 |
| Oren Shtark | 6 | 1 | 0.37 |
| Dvir Tuberg | 7 | 1 | 0.37 |
| Eddie Galfrin | 8 | 1 | 0.37 |
| Irena Gannon | 9 | 1 | 0.37 |
| Adel Shalata | 10 | 1 | 0.37 |
| Zvi U Borochowitz | 11 | 1 | 0.37 |
| Rina Dechter | 12 | 5387 | 703.16 |
| Elizabeth Thompson | 13 | 1 | 0.37 |
| Dan Geiger | 14 | 3371 | 570.49 |