  Detecting genomic footprints of selection is an important step in the
understanding of evolution. Accounting for linkage disequilibrium in genome
scans allows increasing the detection power, but haplotype-based methods
require individual genotypes and are not applicable on pool-sequenced samples.
We propose to take advantage of the local score approach to account for linkage
disequilibrium, accumulating (possibly small) signals from single markers over
a genomic segment, to clearly pinpoint a selection signal, avoiding windowing
methods. This method provided results similar to haplotype-based methods on two
benchmark data sets with individual genotypes. Results obtained for a divergent
selection experiment on behavior in quail, where two lines were sequenced in
pools, are precise and biologically coherent, while competing methods failed:
our approach led to the detection of signals involving genes known to act on
social responsiveness or autistic traits. This local score approach is general
and can be applied to other genome-wide analyzes such as GWAS or genome scans
for selection.
