title: Integration of diverse statistical evidence of gene-trait association in systems biology studies.
abstract: The rapid advancement of high-throughput genomic assay technologies has generated large amounts of diverse genomic data in disparate human populations and diseases. These data provide a unique opportunity for biomedical investigators to systematically study multifaceted aspects of genes' involvement in the biological processes underlying important traits from the systems biology perspective. An important component in such a study is the inference that integrates diverse lines of statistical evidence for gene-trait association from the observed trait values and the massive numbers of measured genomic features. A novel integrated statistical analysis procedure is developed in this paper and is illustrated by an application in studying childhood leukemia.
authors.affiliation: Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA. cheng.cheng@stjude.org
authors.forename: Cheng
authors.initials: C
authors.lastname: Cheng
mesh_terms: D018797:Cell Cycle Proteins / Q000235:genetics / Q000378:metabolism; D002648:Child; D055106:Genome-Wide Association Study; D006801:Humans; D015233:Models, Statistical; D018365:Neoplasm, Residual / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000235:genetics / Q000378:metabolism / Q000473:pathology; D049490:Systems Biology
chemical_list: D018797:Cell Cycle Proteins