A Nonparametric Test of Gene Region Heterogeneity Associated With Phenotype

Jeanne Kowalski Jeanne Kowalski is Assistant Professor, Departments of Oncology and Biostatistics, Johns Hopkins University, Baltimore, MD 21205. Marcello Pagano and Victor DeGruttola are Professors, Department of Biostatistics, Harvard University, Boston, MA 02115. This work was supported in part by grants T32-AI-07358 and R01-AI-280876 from the National Institutes of Health. The authors thank the referees and the editor for helpful suggestions that led to improvements in the article. The authors also thank the members of the AIDS Clinical Trials Group for providing the data used in this article.

Marcello Pagano Jeanne Kowalski is Assistant Professor, Departments of Oncology and Biostatistics, Johns Hopkins University, Baltimore, MD 21205. Marcello Pagano and Victor DeGruttola are Professors, Department of Biostatistics, Harvard University, Boston, MA 02115. This work was supported in part by grants T32-AI-07358 and R01-AI-280876 from the National Institutes of Health. The authors thank the referees and the editor for helpful suggestions that led to improvements in the article. The authors also thank the members of the AIDS Clinical Trials Group for providing the data used in this article.

Victor DeGruttola Jeanne Kowalski is Assistant Professor, Departments of Oncology and Biostatistics, Johns Hopkins University, Baltimore, MD 21205. Marcello Pagano and Victor DeGruttola are Professors, Department of Biostatistics, Harvard University, Boston, MA 02115. This work was supported in part by grants T32-AI-07358 and R01-AI-280876 from the National Institutes of Health. The authors thank the referees and the editor for helpful suggestions that led to improvements in the article. The authors also thank the members of the AIDS Clinical Trials Group for providing the data used in this article.

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.

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A Nonparametric Test of Gene Region Heterogeneity Associated With Phenotype

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A Nonparametric Test of Gene Region Heterogeneity Associated With Phenotype

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