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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
20
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pubmed:dateCreated |
2009-10-12
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pubmed:abstractText |
The current fast growth of genome-wide association studies (GWAS) combined with now common computationally expensive imputation requires the online access of large user groups to high-performance computing resources capable of analyzing rapidly and efficiently millions of genetic markers for ten thousands of individuals. Here, we present a web-based interface--called GRIMP--to run publicly available genetic software for extremely large GWAS on scalable super-computing grid infrastructures. This is of major importance for the enlargement of GWAS with the availability of whole-genome sequence data from the 1000 Genomes Project and for future whole-population efforts.
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pubmed:commentsCorrections |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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|
pubmed:status |
MEDLINE
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pubmed:month |
Oct
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pubmed:issn |
1367-4811
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pubmed:author |
|
|
pubmed:issnType |
Electronic
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pubmed:day |
15
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pubmed:volume |
25
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|
pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
2750-2
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pubmed:dateRevised |
2010-9-27
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pubmed:meshHeading |
|
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pubmed:year |
2009
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|
pubmed:articleTitle |
GRIMP: a web- and grid-based tool for high-speed analysis of large-scale genome-wide association using imputed data.
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pubmed:affiliation |
Department of Internal Medicine, Erasmus MC, Dr. Molewaterplein 50, 3015GE Rotterdam, The Netherlands.
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pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
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