A Composite of Multiple Signals Distinguishes Causal Variants in Regions of Positive Selection

Author:

Grossman Sharon R.12,Shylakhter Ilya12,Karlsson Elinor K.12,Byrne Elizabeth H.12,Morales Shannon123,Frieden Gabriel1,Hostetter Elizabeth12,Angelino Elaine14,Garber Manuel2,Zuk Or2,Lander Eric S.245,Schaffner Stephen F.2,Sabeti Pardis C.124

Affiliation:

1. Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.

2. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.

3. Mount Sinai School of Medicine, New York, NY 10029, USA.

4. Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.

5. Department of Biology, MIT, Cambridge, MA 02139, USA.

Abstract

Pinpointing Genetic Selection The human genome contains hundreds of regions with evidence of recent positive natural selection, yet, for all but a handful of cases, the underlying advantageous mutation remains unknown. Current methods to detect the signal of selection often results in the identification of a broad genomic region containing many candidate regions that vary among individuals. By combining existing statistical methods, Grossman et al. (p. 883 , published online 7 January) developed a method, termed Composite of Multiple Signals, which can increase the ability to pinpoint the specific variant under selection. Several candidate regions under selection in human populations were identified.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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