A cautionary note on the use of unsupervised machine learning algorithms to characterise malaria parasite population structure from genetic distance matrices

• Main Authors: James A. Watson, Aimee R. Taylor, Elizabeth A. Ashley, Arjen Dondorp, Caroline O. Buckee, Nicholas J. White, Chris C. Holmes
• Other Authors: Harvard T.H. Chan School of Public Health
• Format: Article
• Published: 2020
• Subjects: Agricultural and Biological Sciences; Biochemistry, Genetics and Molecular Biology; Medicine
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/59807
• Institution: Mahidol University

© 2020 Watson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Genetic surveillance of malaria parasites s...