SAI: A Python Package for Statistics for Adaptive Introgression
More On Article
- FWF funding for open-access publication Methodological Innovations in pXRF Studies
- Up and down the hill: Hillforts and dry stone wall enclosures on the Kvarner Islands of Cres and Lošinj in remote sensing data
- A microcontextual investigation of Later Stone Age ash deposits and associated interment of human remains at Faraoskop Rock Shelter, South Africa
- 35 Jahre “Archäologie Österreichs”. Ein Rück-und Ausblick auf die Wissensvermittlung durch Printmedien der ÖGUF.
- HEAS Members Publish GENOVIS: a Python package for the visualization of population genetic analyses
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.