Stanford University HIV Drug Resistance Database - A curated public database designed to represent, store, and analyze the divergent forms of data underlying HIV drug resistance.

Genotypic Predictors of Human Immunodeficiency Virus Type 1 Drug Resistance

Rhee SY, Taylor J, Wadhera G, Ben-Hur A, Brutlag DL, Shafer RW., Proceedings of National Academy of Sciences of the United States of America, Oct 25, 2006.

Data

  1. Sets of mutations [Table 1]:

  2. Genotype-phenotype correlation data sets:

  3. Phenotype cut-offs between susceptible, low/intermediate resistance and high-level resistance for each drug

Results

  1. Summary of 10 x 5 fold-cross validation results:
Tables
  1. Prediction accuracy [Table 3]
  2. Number of highly discordant predictions according to mutation set and regression method [Table 4]
  3. Highly Discordant Isolates: Predictions based on Least Angle Regression (LARS) Using Nonpolymorphic Treatment Selected Mutations [Table 5]
  4. Correlation coefficients (r2) between actual and predicted result according to regression method and mutation dataset [Table 6]
  5. Mean squared error between actual and predicted result according to regression method and mutation dataset [Table 7]
  6. Regression coefficients for the PI treatment-selected mutations [Table 8], the NRTI treatment-selected mutations [Table 9] and the NNRTI treatment-selected mutations [Table 10] in the Least Squares Regression (LSR),Support Vector Regression (SVR), and Least Angle Regression (LARS) Models
Figures
  1. Least-squares regression coefficients for protease inhibitor [figure 1A], nucleoside RT inhibitor [figure 1B] and non-nucleoside RT inhibitor [figure 1C] treatment-selected mutations
  2. Distribution in the number of nonpolymorphic TSMs [figure 2A] and expert panel mutations [figure 2B] per isolate
  3. Rate of learning using regression and nonpolymorphic treatment-selected mutations (TSMs) [figure 3]
  4. Regression coefficients for each of the PI, NRTI and NNRTI TSMs determined by different regression methods [figure 4]

    [figure legends]