Open AccessStatistical tests of selective neutrality in the age of genomics
Author(s) -
NIELSEN RASMUS
Publication year - 2001
Publication title -
heredity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.441
H-Index - 118
eISSN - 1365-2540
pISSN - 0018-067X
DOI - 10.1046/j.1365-2540.2001.00895.x
Subject(s) - biology , nonsynonymous substitution , selection (genetic algorithm) , evolutionary biology , genomics , neutral theory of molecular evolution , computational biology , statistical hypothesis testing , population genomics , population , genetics , effective population size , genome , statistics , genetic variation , machine learning , computer science , gene , mathematics , demography , sociology
Examining genomic data for traces of selection provides a powerful tool for identifying genomic regions of functional importance. Many methods for identifying such regions have focused on conserved sites. However, positive selection may also be an indication of functional importance. This article provides a brief review of some of the statistical methods used to detect selection using DNA sequence data or other molecular data. Statistical tests based on allelic distributions or levels of variability often depend on strong assumptions regarding population demographics. In contrast, tests based on comparisons of the level of variability in nonsynonymous and synonymous sites can be constructed without demographic assumptions. Such tests appear to be useful for identifying specific regions or specific sites targeted by selection.