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

A New Local Score Based Method Applied to Behavior-divergent Quail Lines  Sequenced in Pools Precisely Detects Selection Signatures on Genes Related to  Autism