theLongLab/CATE: CATE and Apollo

CATE's newest release comes complete with Apollo.

Apollo is a comprehensive simulation software for epidemics in a population, complete with within-host dynamics. CATE, our large-scale parallel processing architecture, powers it.

A detailed user manual describing how to use CATE is provided below:

Apollo's user manual

Apollo also comes with a video tutorial, you can either download and watch using the GitHub repo's version or watch online via Vimeo:. The links to both are below:

GitHub repo tutorial

Vimeo link

You can cite CATE in your work using:

Perera, D., Reisenhofer, E., Hussein, S., Higgins, E., Huber, C. D., & Long, Q. (2023). CATE: A fast and scalable CUDA implementation to conduct highly parallelized evolutionary tests on large scale genomic data. Methods in Ecology and Evolution, 00, 1–15. https://doi.org/10.1111/2041-210X.14168.

Citation of the code with Apollo can be done via the Zenodo link below:

Apollo is currently available on preprint. If you do use it, please cite the preprint:

Apollo: A comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell Deshan Perera, Evan Li, Frank van der Meer, Tarah Lynch, John Gill, Deirdre L Church, Christian D. Huber, Guido van Marle, Alexander Platt, Quan Long bioRxiv 2024.10.07.617101; doi: https://doi.org/10.1101/2024.10.07.617101