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Detecting strong positive selection in the genome
Author(s) -
STEPHAN WOLFGANG
Publication year - 2010
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/j.1755-0998.2010.02869.x
Subject(s) - biology , linkage disequilibrium , panmixia , genome , selection (genetic algorithm) , genetics , evolutionary biology , single nucleotide polymorphism , computational biology , genetic variation , genotype , genetic structure , machine learning , gene , computer science
New statistical tests have been developed in the past decade that enable us to infer evidence of recent strong positive selection from genome‐wide data on single‐nucleotide polymorphism and to localize the targets of selection in the genome. Based on these tests, past demographic events that led to distortions of the site‐frequency spectrum of variation can be distinguished from selection, in particular if linkage disequilibrium is taken into account. These methods have been successfully applied to species from which complete sequence information and polymorphism data are available, including Drosophila melanogaster , humans, and several plant species. To make full use of the available data, however, the tests that were primarily designed for panmictic populations need to be extended to spatially structured populations.