Identifying Selections Operating on HIV-1 Reverse Transcriptase via Uniform Manifold Approximation and Projection
| Title: | Identifying Selections Operating on HIV-1 Reverse Transcriptase via Uniform Manifold Approximation and Projection |
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| Authors: | Qamar, Shefali, Camps, Manel, Kim, Jay |
| Publication Year: | 2022 |
| Collection: | Computer Science Quantitative Biology |
| Subject Terms: | Quantitative Biology - Genomics, Computer Science - Computational Engineering, Finance, and Science, Computer Science - Machine Learning, 68U99, 62P10, 92D15, 92D20, I.2.1, J.3 |
| More Details: | We analyze 14,651 HIV1 reverse transcriptase (HIV RT) sequences from the Stanford HIV Drug Resistance Database labeled with treatment regimen in order to study the evolution this enzyme under drug selection in the clinic. Our goal is to identify distinct sectors of HIV RT's sequence space that are undergoing evolution as a way to identify individual selections and/or evolutionary solutions. We utilize Uniform Manifold Approximation and Projection (UMAP), a graph-based dimensionality reduction technique uniquely suited for the detection of non-linear dependencies and visualize the results using an unsupervised clustering algorithm based on density analysis. Our analysis produced 21 distinct clusters of sequences. Supporting the biological significance of these clusters, they tend to represent phylogenetically related sequences with strong correspondence to distinct treatment regimens. Thus, this method for visualization of areas of HIV RT undergoing evolution can help infer information about selective pressures, although it is correlative. The mutation signatures associated with each cluster may represent the higher-order epistatic context facilitating these evolutionary pathways, information that is generally not accessible by other types of mutational co-dependence analyses. Comment: To be published in ICBRA 2022 ACM Conference Proceedings (ISBN: 978-1-4503-8426-1); 15 pages, 4 figures, 2 tables; Code available at github.com/shefaliqamar/HIV-Epistatic |
| Document Type: | Working Paper |
| Access URL: | http://arxiv.org/abs/2210.00345 |
| Accession Number: | edsarx.2210.00345 |
| Database: | arXiv |
| Description not available. |