SAI: A Python Package for Statistics for Adaptive Introgression
More On Article
- Reading All the Lines of Archaeological Legacy Records
- Early Gravettian genomic data from Western Europe reveal population movements before the LGM
- At the onset of the Late Gravettian: An updated chronology and stratigraphy for the multi-layered Gravettian open-air site Grub-Kranawetberg I (Austria).
- New Chronology Sheds Light on Human Occupation just before the onset of the Last Glacial Maximum
- Fire, temperature control, and silcrete heat treatment at Diepkloof and Mertenhof Rock Shelters, West Coast, South Africa
Huang, X., Chen, S., Hackl, J., Kuhlwilm, M., 2025. SAI: A Python Package for Statistics for Adaptive Introgression. Molecular Biology and Evolution.
Abstract
Adaptive introgression is an important evolutionary process, which can be identified with widely used summary statistics, such as the number of uniquely shared sites and the quantile of the derived allele frequencies in such sites. However, these as well as more recently developed statistics such as D+ and Danc, still lack accessible implementations. Here, we present SAI, a Python package for computing these statistics along with a new statistic, DD, and demonstrate its application on two datasets. First, using the 1000 Genomes Project data, we replicated previously reported candidate regions and identified additional ones, including a region detected by studies using supervised deep learning. Second, we investigated bonobo introgression into central chimpanzees and identified candidate genes, finding one region that overlaps a high-frequency Denisovan-introgressed haplotype block reported in modern Papuans. This is an intriguing co-occurrence across divergent lineages, underscoring the role of adaptive introgression in evolution.