ArticleBioinformatics (Oxford, England)2010
HIV classification using the coalescent theory.
Article in Bioinformatics (Oxford, England), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genetic diversity and drug resistance mutations of HIV-1 in Ghana: a systematic review of two decades.BMC infectious diseases · 2026Pooled it
- Revisiting the recombinant history of HIV-1 group M with dynamic network community detection.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- High Degree of HIV-1 Group M (HIV-1M) Genetic Diversity within Circulating Recombinant Forms: Insight into the Early Events of HIV-1M Evolution.Journal of virology · 2015Article
- A model-based information sharing protocol for profile Hidden Markov Models used for HIV-1 recombination detection.BMC bioinformatics · 2014Article
- Current Trends of HIV Recombination Worldwide.Infectious disease reports · 2013Review
- Phylodynamics of the HIV-1 CRF02_AG clade in Cameroon.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2012Article
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Authors and funding
8 authors.
Funding
Abstract
motivationExisting coalescent models and phylogenetic tools based on them are not designed for studying the genealogy of sequences like those of HIV, since in HIV recombinants with multiple cross-over points between the parental strains frequently arise. Hence, ambiguous cases in the classification of HIV sequences into subtypes and circulating recombinant forms (CRFs) have been treated with ad hoc methods in lack of tools based on a comprehensive coalescent model accounting for complex recombination patterns.
resultsWe developed the program ARGUS that scores classifications of sequences into subtypes and recombinant forms. It reconstructs ancestral recombination graphs (ARGs) that reflect the genealogy of the input sequences given a classification hypothesis. An ARG with maximal probability is approximated using a Markov chain Monte Carlo approach. ARGUS was able to distinguish the correct classification with a low error rate from plausible alternative classifications in simulation studies with realistic parameters. We applied our algorithm to decide between two recently debated alternatives in the classification of CRF02 of HIV-1 and find that CRF02 is indeed a recombinant of Subtypes A and G. AVAILABILITY: ARGUS is implemented in C++ and the source code is available at http://gobics.de/software.
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