Identifying Signatures of Selection in Genetic Time Series
We develop a rigorous test for natural selection based on allele frequencies sampled from a population over multiple time points. We demonstrate that the standard method of estimating selection coefficients in this setting, and the associated chi-squared likelihood-ratio test of neutrality, is biased and it therefore does not provide a reliable test of selection. We introduce two methods to correct this bias, and we demonstrate that the new methods have power to detect selection in practical parameter regimes, such as those encountered in fitness assays of microbial populations. Our analysis is limited to a single diallelic locus, assumed independent of all other loci in a genome, which is again relevant to simple competition assays of laboratory and natural isolates; other techniques will be required to detect selection in time series of co-segregating, linked loci.