Mining data from 1000 genomes to identify the causal variant in regions under positive selection
Name
Grossman-2010-Mining data from 1000 genomes to identify the causal variant.pdf
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166.26 KB
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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-
Date Issued
October 2010
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
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.
MIT Department
Whitaker College of Health Sciences and Technology
Massachusetts Institute of Technology. Department of Biology
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Creative Commons Attribution
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DOI of Published Version
http://genomebiology.com/2010/11/S1/I22
