%0 Journal Article %1 PavlosPavlidis04202010 %A Pavlidis, Pavlos %A Jensen, Jeffrey D. %A Stephan, Wolfgang %D 2010 %J Genetics %K test_of_selection %P genetics.110.116459 %R 10.1534/genetics.110.116459 %T Searching for Footprints of Positive Selection in Whole-genome SNP Data from Non-equilibrium Populations %U http://www.genetics.org/cgi/content/abstract/genetics.110.116459v1 %X A major goal of population genomics is to reconstruct the history of natural populations and to infer the neutral and selective scenarios that can explain the present-day polymorphism patterns. However, the separation between neutral and selective hypotheses has proven hard, mainly because both may predict similar patterns in the genome. The present study focuses on the development of methods that can be used to distinguish neutral from selective hypotheses in equilibrium and non-equilibrium populations. These methods utilize a combination of statistics based on the site frequency spectrum (SFS) and linkage disequilibrium (LD). We investigate the patterns of genetic variation along recombining chromosomes using a multitude of comparisons between neutral and selective hypotheses, such as selection or neutrality in equilibrium and non-equilibrium populations, and recurrent selection models. We perform hypothesis testing using the classical p-value approach, but we also introduce methods from the machine learning field. We demonstrate that the combination of SFS- and LD-based statistics increases the power to detect recent positive selection in populations that have experienced past demographic changes.

@article{PavlosPavlidis04202010, abstract = {A major goal of population genomics is to reconstruct the history of natural populations and to infer the neutral and selective scenarios that can explain the present-day polymorphism patterns. However, the separation between neutral and selective hypotheses has proven hard, mainly because both may predict similar patterns in the genome. The present study focuses on the development of methods that can be used to distinguish neutral from selective hypotheses in equilibrium and non-equilibrium populations. These methods utilize a combination of statistics based on the site frequency spectrum (SFS) and linkage disequilibrium (LD). We investigate the patterns of genetic variation along recombining chromosomes using a multitude of comparisons between neutral and selective hypotheses, such as selection or neutrality in equilibrium and non-equilibrium populations, and recurrent selection models. We perform hypothesis testing using the classical p-value approach, but we also introduce methods from the machine learning field. We demonstrate that the combination of SFS- and LD-based statistics increases the power to detect recent positive selection in populations that have experienced past demographic changes. }, added-at = {2010-04-22T06:55:54.000+0200}, author = {Pavlidis, Pavlos and Jensen, Jeffrey D. and Stephan, Wolfgang}, biburl = {https://www.bibsonomy.org/bibtex/274a7ea813ee0a25d40ee84d1e182d954/peter.ralph}, description = {Searching for Footprints of Positive Selection in Whole-genome SNP Data from Non-equilibrium Populations -- Pavlidis et al., 10.1534/genetics.110.116459 -- Genetics}, doi = {10.1534/genetics.110.116459}, interhash = {6bebb05e362dd165ac0f9762f68b2060}, intrahash = {74a7ea813ee0a25d40ee84d1e182d954}, journal = {Genetics}, keywords = {test_of_selection}, pages = {genetics.110.116459}, timestamp = {2010-04-22T06:56:14.000+0200}, title = {Searching for Footprints of Positive Selection in Whole-genome {SNP} Data from Non-equilibrium Populations}, url = {http://www.genetics.org/cgi/content/abstract/genetics.110.116459v1}, year = 2010 }