Information theoretic inference of magnitude and direction of gene flow in metapopulation networks using nyemtaay, with potential for applications in metastasizing cancer clonal cell origin analysis

BackgroundWe introduce nyemtaay, a Python package for the calculation of classical population genetic statistics and inference of gene flow network connections and directionality in metapopulation networks using information theory. This genetic information flow network inference approach provided here is the only existing implementation of [1], and is applicable not only to ecological and evolutionary organism and landscape scale studies, but also has potential applications in, for example, cancer biology for analyzing clonal cell origins in metastasizing tumors. ResultsWe demonstrate this potential through simulations and an analysis of metastasizing cancer cell lineages, showcasing its ability to identify the tissue site of origin in cancer networks. This work highlights the importance of considering demographic history and founder effects in interpreting gene flow directionality, and the benefits of this understanding in allowing application of this approach to gene flow network modeling to reach a broader range of domains. Conclusionsnyemtaay is available under the MIT license from its public repository (https://github.com/aortizsax/nyemtaay), and can be installed locally using the Python package manager pip.