Characterizing the relationship between HIV-1 genotype and phenotype: prediction-based classification.
This paper establishes a framework for understanding the complex relationships between HIV-1 genotypic markers of resistance to antiretroviral drugs and clinical measures of disease progression. A new classification scheme based on the probabilities of how new patients will respond to antiretroviral therapy given the available data is proposed as a method for distinguishing among groups of viral sequences. This approach draws from existing cluster analysis, discriminant analysis, and recursive partitioning techniques and requires a model relating genotypic characteristics to phenotypic response. A data set of 2,746 sequences and the corresponding Indinavir 50% inhibitory concentrations are described and used for illustrative purposes.
Foulkes
A S
AS
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. foulkes@sdac.harvard.edu
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Gruttola V
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D000595:Amino Acid Sequence; D016000:Cluster Analysis; D024882:Drug Resistance, Viral / Q000235:genetics; D005838:Genotype; D015658:HIV Infections / Q000188:drug therapy*; D017320:HIV Protease Inhibitors / Q000627:therapeutic use*; D015497:HIV-1 / Q000145:classification* / Q000187:drug effects / Q000235:genetics; D006801:Humans; D019469:Indinavir / Q000627:therapeutic use*; D020128:Inhibitory Concentration 50; D008957:Models, Genetic; D008969:Molecular Sequence Data; D005810:Multigene Family; D015999:Multivariate Analysis; D009154:Mutation; D010641:Phenotype; D011237:Predictive Value of Tests; D014766:Viremia / Q000188:drug therapy
D017320:HIV Protease Inhibitors; D019469:Indinavir