A nonparametric test of gene region heterogeneity associated with phenotype

J. Kowalski, M. Pagano, V. DeGruttola

Research output: Contribution to journalArticlepeer-review

Abstract

High-dimensional statistical problems arise in the investigation of the relationship between reduced sensitivity to antiretroviral drugs among human immunodeficiency virus-infected patients and viral genotypic patterns obtained from blood samples. This article develops a nonparametric approach for analyzing gene region heterogeneity associated with drug-resistance phenotype. The method is based on the distribution of distances between viral genetic sequences. The distance measures used are sufficiently flexible to allow weighting of locations within a gene region, as well as weighting of residue types within a location. The weighting may reflect covariability between locations and between residues within a location. The approach to inference presented extends U statistic theory to multivariate one- and two-sample cases, which leads to exact tests based on permutation theory and their asymptotic counterparts. These methods are applied to data from a study conducted by the AIDS Clinical Trials Group that investigated altered viral susceptibility to protease inhibitor drugs.

Original languageEnglish (US)
Pages (from-to)398-408
Number of pages11
JournalJournal of the American Statistical Association
Volume97
Issue number458
DOIs
StatePublished - 2002

Keywords

  • AIDS
  • Distances
  • Gene sequence
  • Human immunodeficiency virus
  • Permutation inference
  • Protease
  • RNA
  • U statistics

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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