title: A fast and powerful tree-based association test for detecting complex joint effects in case-control studies.
abstract: BACKGROUND
  Multivariate tests derived from the logistic regression model are widely used to assess the joint effect of multiple predictors on a disease outcome in case-control studies. These tests become less optimal if the joint effect cannot be approximated adequately by the additive model. The tree-structure model is an attractive alternative, as it is more apt to capture non-additive effects. However, the tree model is used most commonly for prediction and seldom for hypothesis testing, mainly because of the computational burden associated with the resampling-based procedure required for estimating the significance level.
  
  
  RESULTS
  We designed a fast algorithm for building the tree-structure model and proposed a robust TREe-based Association Test (TREAT) that incorporates an adaptive model selection procedure to identify the optimal tree model representing the joint effect. We applied TREAT as a multilocus association test on >20 000 genes/regions in a study of esophageal squamous cell carcinoma (ESCC) and detected a highly significant novel association between the gene CDKN2B and ESCC ([Formula: see text]). We also demonstrated, through simulation studies, the power advantage of TREAT over other commonly used tests.
  
  
  METHODS
  The package TREAT is freely available for download at http://www.hanzhang.name/softwares/treat, implemented in C++ and R and supported on 64-bit Linux and 64-bit MS Windows.
  
  
  BACKGROUND
  yuka@mail.nih.gov
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.
authors.forename: Han
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.
authors.forename: William
authors.initials: W
authors.lastname: Wheeler
authors.affiliation: Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USABiostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.
authors.forename: Zhaoming
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.
authors.forename: Philip R
authors.initials: PR
authors.lastname: Taylor
authors.affiliation: Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD 20850, USA, Information Management Services, Inc., Silver Spring, Maryland 20904, USA, and Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland 20877, USA.
authors.forename: Kai
authors.initials: K
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000235:genetics; D016022:Case-Control Studies; D019295:Computational Biology / Q000379:methods*; D050762:Cyclin-Dependent Kinase Inhibitor p15 / Q000235:genetics; D003663:Decision Trees; D004938:Esophageal Neoplasms / Q000235:genetics; D020022:Genetic Predisposition to Disease / Q000235:genetics; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D020641:Polymorphism, Single Nucleotide; D013997:Time Factors
chemical_list: D050762:Cyclin-Dependent Kinase Inhibitor p15