Collaborators: Kevin Hu, Tiana Pereria, Michael Lanthier
Drug resistance is a continuing problem when treating HIV/AIDS. Because of the very high mutation rates of HIV, drug resistance is developed extremely quickly. In order to best treat HIV, being able to identify mutations associated with drug resistance is extremely important. Through the use of a longitudinal data set of 1,700 patients, we performed analysis of HIV reverse transcriptase to identify positively selected positions that may incur drug resistance.
For a more indepth description of the project, view the Project_Report.pdf file. This project was done under the advisement of Jay Kim, a Phd candidate in the Biomolecular Engineering Departement at the University of California Santa Cruz(https://users.soe.ucsc.edu/~jaykim/).
The program runs in Python 3. Backwards compatability is not guaranteed.
Please don't make any important scientific decisions based on this program and our report. We are just undergraduates and errors may exist in everything we do.