This code is provided as a companion to the paper: A review of UMAP in population genetics. Diaz-Papkovich, A., Anderson-Trocmé, L. & Gravel, S. J Hum Genet (2020). https://doi.org/10.1038/s10038-020-00851-4
A free access version of this paper is available at: https://rdcu.be/b8vFr
For our original publication on using UMAP to study population structure in genetic data, see: UMAP reveals cryptic population structure and phenotype heterogeneity in large genomic cohorts. Diaz-Papkovich A, Anderson-Trocmé L, Ben-Eghan C, Gravel S. PLoS Genet 15(11): e1008432 (2019). https://doi.org/10.1371/journal.pgen.1008432 and the Github repo: https://github.com/diazale/gt-dimred
For our follow-up paper on clustering population structure using UMAP, see: Topological stratification of continuous genetic variation in large biobanks. Diaz-Papkovich, A. et al. bioRxiv (2023). https://www.biorxiv.org/content/10.1101/2023.07.06.548007.abstract and the github repo: https://github.com/diazale/topstrat
For the original UMAP paper, see: UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. Leland McInnes, John Healy, James Melville. arXiv:1802.03426 (2018). https://arxiv.org/abs/1802.03426