A statistical model for HIV-1 sequence classification using the subtype analyser (STAR)

Academic Article


  • Motivation: HIV-1 antiretroviral drug resistance testing produces large amounts of HIV-1 protease and reverse transcriptase sequences. These provide an excellent resource to study the incidence, spread and clinical significance of HIV-1 subtypes. We have produced a program, Subtype Analyser (STAR) that rapidly and accurately subtypes HIV-1. Here we have determined a robust and statistically validated model for subtype assignment. Results: We have significantly extended our HIV-1 subtyping tool (STAR), such that each query sequence when evaluated against subtype profile alignments, returns a discriminating score based on the ratio of subtype positive to negative amino acid positions. These scores were transformed into a Z-score distribution and evaluated. Of the 141 sequences used to define the subtype alignments, 98% were correctly reclassified. Inclusion of additional recombination detection within STAR increased the detection of known recombinant sequences to 95%. © The Author 2005. Published by Oxford University Press. All rights reserved.
  • Published In

  • Bioinformatics  Journal
  • Digital Object Identifier (doi)

    Author List

  • Myers RE; Gale CV; Harrison A; Takeuchi Y; Kellam P
  • Start Page

  • 3535
  • End Page

  • 3540
  • Volume

  • 21
  • Issue

  • 17