Publication | Open Access
A Composite of Multiple Signals Distinguishes Causal Variants in Regions of Positive Selection
520
Citations
16
References
2010
Year
Behavioral Decision MakingGeneticsNatural SelectionGenomicsUnderlying GeneCausal InferenceMolecular EcologyHuman VariationPositive SelectionBiostatisticsPublic HealthDecision TheoryStatisticsCausal ModelHaplotype DeterminationBehavioral SciencesMultiple SignalsSelection BiasNovel Causal VariantsMedicineStatistical GeneticsGenetic VariationCausal ReasoningPopulation GeneticsAllelic VariantEvolutionary BiologyStatistical InferenceCausalityPopulation GenomicsDecision Science
The human genome contains hundreds of regions whose patterns of genetic variation indicate recent positive natural selection, yet for most the underlying gene and the advantageous mutation remain unknown. We developed a method, composite of multiple signals (CMS), that combines tests for multiple signals of selection and increases resolution by up to 100-fold. By applying CMS to candidate regions from the International Haplotype Map, we localized population-specific selective signals to 55 kilobases (median), identifying known and novel causal variants. CMS can not just identify individual loci but implicates precise variants selected by evolution.
| Year | Citations | |
|---|---|---|
Page 1
Page 1