Controlling the false positive rate in multilocus genome scans for selection

¹ Cornell University

^* To whom correspondence should be addressed. E-mail: kt234{at}cornell.edu.

Submitted on August 9, 2006
Revised on September 25, 2006
Accepted on 18 October 2006

	Abstract

Rapid typing of genetic variation at many regions of the genome is an efficient way to survey variability in natural populations in an effort to identify segments of the genome which have experienced recent natural selection. Following such a genome scan, individual regions may be chosen for further sequencing and a more detailed analysis of patterns of variability, often in order to perform a parametric test for selection and to estimate the strength of a recent selective sweep. We show here that not accounting for the ascertainment of loci in such analyses leads to false inference of natural selection because the procedure of choosing unusual loci (in comparison to the rest of the genome scan data) selects regions of the genome with genealogies similar to those expected under models of recent directional selection, even when the true model is selective neutrality. We describe a simple and efficient correction for this ascertainment bias, which restores the false-positive rate to near-nominal levels. For the parameters considered here, we find that obtaining a test with the expected distribution of <it>p</it>-values depends on accurately accounting both for ascertainment of regions and for demography. Finally, we use simulations to explore the utility of relying on outlier loci to detect recent selective sweeps. We find that measures of diversity and of population differentiation are more effective than summaries of the site-frequency spectrum, and that sequencing larger regions (2.5 kilobase pairs) in genome scan studies leads to more power to detect recent selective sweeps.

Key Words: coalescent simulation, demography, selective sweeps

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