Geno2pheno

Geno2pheno predicts HIV phenotypic drug resistance and coreceptor usage from viral genotypic data, enabling interpretation of pol gene (protease and reverse transcriptase) mutations for antiretroviral susceptibility.

Key Features:

• Genotype-Phenotype Correlation: Constructs regression models from 650 matched genotype-phenotype pairs to predict phenotypic drug resistance from genotypic information.
• Scoring Functions: Employs two distinct scoring functions derived from different sets of predicted phenotypes to standardize resistance measures across antiretroviral drugs.
• Deviance Analysis: Reports relative deviance by comparing predicted values against samples from 178 treatment-naive patients.
• Probability Density Estimation: Estimates the probability density of 2000 predicted phenotypes to define susceptible and resistant subpopulations and to compute the likelihood that a given prediction belongs to the resistant subpopulation.

Scientific Applications:

• Antiretroviral therapy optimization: Predicts phenotypic drug resistance from genotypes to support tailoring of antiretroviral regimens and to help reduce the emergence of drug-resistant HIV strains.
• HIV tropism, pathogenesis, and vaccine research: Predicts coreceptor usage to inform studies of viral tropism, HIV pathogenesis, and vaccine development.

Methodology:

Constructs regression models from 650 genotype-phenotype pairs, derives two scoring functions from modeled predicted phenotypes, estimates probability density from 2000 predicted phenotypes to define susceptible/resistant subpopulations, and compares predictions to 178 treatment-naive patient samples to report relative deviance.