Detecting interacting mutation clusters in HIV-1 drug resistance

Yu Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Understanding the genetic basis of HIV-1 drug resistance is essential for antiretroviral drug development. We analyzed drug resistant mutations in HIV-1 protease and reverse transcriptase under 18 drug treatments. The analysis is challenging because there is a large number of possible mutation combinations that may jointly affect drug resistance. The mutations are also strongly correlated, imposing inference difficulties such as multi-colinearity issues. We applied a novel Bayesian algorithm to the drug resistance data. Our method efficiently identified clusters of mutations in HIV-1 protease and reverse transcriptase that are strongly and directly associated with drug resistance. In addition to marginal associations, we detected strong interactions among mutations at distant protein locations. Most identified protein positions are crossresistant to several drugs of the same types. The effects of interactions are mostly negative, suggesting a threshold mechanism for the genetics underlying HIV drug resistance. Our method is among the first to produce detailed structures of marginal and interactive associations in HIV-1 drug resistance studies, and is generally suitable for detecting high-order interactions in large-scale datasets with complex dependencies.

Original languageEnglish (US)
Title of host publicationBIOINFORMATICS 2013 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms
Pages34-43
Number of pages10
StatePublished - May 27 2013
EventInternational Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2013 - Barcelona, Spain
Duration: Feb 11 2013Feb 14 2013

Publication series

NameBIOINFORMATICS 2013 - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms

Other

OtherInternational Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2013
CountrySpain
CityBarcelona
Period2/11/132/14/13

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics
  • Modeling and Simulation

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