TY - JOUR T1 - diploS/HIC: an updated approach to classifying selective sweeps JF - bioRxiv DO - 10.1101/267229 SP - 267229 AU - Andrew D. Kern AU - Daniel R. Schrider Y1 - 2018/01/01 UR - http://biorxiv.org/content/early/2018/02/18/267229.abstract N2 - Identifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective sweeps in genomes on the basis of patterns of genetic variation surrounding a window of the genome. While S/HIC was shown to be both powerful and precise, the utility of S/HIC was limited by the use of phased genomic data as input. In this report we describe a deep learning variant of our method, diploS/HIC, that uses unphased genotypes to accurately classify genomic windows. diploS/HIC is shown to be quite powerful even at moderate to small sample sizes ER -