A spatially aware likelihood test to detect sweeps from haplotype distributions

The inference of positive selection in genomes is a problem of great
interest in evolutionary genomics. By identifying putative regions of the
genome that contain adaptive mutations, we are able to learn about the
biology of organisms and their evolutionary history. Here we introduce a
composite likelihood method that identifies recently completed or ongoing
positive selection by searching for extreme distortions in the spatial
distribution of the haplotype frequency spectrum along the genome relative
to the genome-wide expectation taken as neutrality. Furthermore, the
method simultaneously infers two parameters of the sweep: the number of
sweeping haplotypes and the “width” of the sweep, which is related to the
strength and timing of selection. We demonstrate that this method
outperforms the leading haplotype-based selection statistics, though
strong signals in low-recombination regions merit extra scrutiny. As a
positive control, we apply it to two well-studied human populations from
the 1000 Genomes Project and examine haplotype frequency spectrum patterns
at the LCT and MHC loci. We also apply it to a data set of brown rats
sampled in NYC and identify genes related to olfactory perception. To
facilitate use of this method, we have implemented it in user-friendly
open source software.