Amber Biology principals are lead authors on new peer-reviewed publication

As part of the collaborative development team, Amber Biology is proud to announce our open-access peer-reviewed publication "PyPop: a mature open-source software pipeline for population genomics" in the journal Frontiers in Immunology

The publication is a companion to the recent stable 1.0.0 release of the open-source population genetics software pipeline, PyPop. From the abstract:

Python for Population Genomics (PyPop) is a software package that processes genotype and allele data and performs large-scale population genetic analyses on highly polymorphic multi-locus genotype data...these tests are central to genetic studies of disease association.. Here, we present PyPop 1.0.0, a new major release of the package, which implements new features using the more robust infrastructure of GitHub, and is distributed via the industry-standard Python Package Index

The first publication to feature both Amber Biology principals, Alex Lancaster and Gordon Webster, as authors, Amber Biology had also been previously hired as part of an international immunogenetics workshop to extend PyPop to handle the increasingly larger population datasets generated by the research community. Alex is the lead author on this new publication, as well as the primary software maintainer.

Along with Amber Biology, the collaborative team includes co-authors from the University of Vermont (Richard Single and Michael Mariani), UCSF (Steven J. Mack) and Lawrence Livermore National Laboratory (Vanessa Sochat).

This publication is particularly exciting for Amber Biology, as a big supporter of open source tools for open science, as it represents the culmination of sustained efforts over several years.

Full citation:

Lancaster AK, Single RM, Mack SJ, Sochat V, Mariani MP and Webster GD (2024) PyPop: a mature open-source software pipeline for population genomics. Front. Immunol. 15:1378512. doi: 10.3389/fimmu.2024.1378512

The full paper is online: https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1378512/full and the the GitHub repository can be found here: https://github.com/alexlancaster/pypop