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Mining data from 1000 genomes to identify the causal variant in regions under positive selection

Author(s)
Grossman, Sharon Rachel; Karlsson, Elinor K.; Tabrizi, Shervin; Andersen, Kristian G.; Rinn, John L.; Lander, Eric S.; Schaffner, Steve; Sabeti, Pardis C.; 1000 Genomes Project Consortium; Shlyakhter, Ilya, 1975-; ... Show more Show less
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Abstract
The human genome contains hundreds of regions in which the patterns of genetic variation indicate recent positive natural selection, yet for most of these the underlying gene and the advantageous mutation remain unknown. We recently reported the development of a method, Composite of Multiple Signals (CMS), that combines tests for multiple signals of natural selection and increases resolution by up to 100-fold.
Date issued
2010-10
URI
http://hdl.handle.net/1721.1/69960
Department
Whitaker College of Health Sciences and Technology; Massachusetts Institute of Technology. Department of Biology
Journal
Genome Biology
Publisher
BioMed Central Ltd.
Citation
Grossman, Shari et al. "Mining data from 1000 genomes to identify the causal variant in regions under positive selection." Genome Biology 2010, 11(Suppl 1):I22 (11 October 2010).
Version: Final published version
ISSN
1465-6906
1474-7596

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