A mixture model approach for the analysis of microarray gene expression data

Authors:
David B. Allison;Gary L. Gadbury;Moonseong Heo;José R. Fernández;Cheol-Koo Lee;Thomas A. Prolla;Richard Weindruch
Affiliations:
Department of Biostatistics and Center for Research on Clinical Nutrition, University of Alabama at Birmingham, Ryals Public Health Bldg, Suite 327, 1665 University Ave. UAB Station, Birmingham, A ...;Department of Mathematics and Statistics, University of Missouri--Rolla, USA;Obesity Research Center, St. Luke's/Roosevelt Hospital, Institute of Human Nutrition, Columbia University College of Physicians & Surgeons, New York, NY, USA;Obesity Research Center, St. Luke's/Roosevelt Hospital, Institute of Human Nutrition, Columbia University College of Physicians & Surgeons, New York, NY, USA;Environmental Toxicology Center, University of Wisconsin, Madison, WI, USA and Departments of Genetics and Medical Genetics, University of Wisconsin, Madison, WI, USA;Departments of Genetics and Medical Genetics, University of Wisconsin, Madison, WI, USA;Department of Medicine and the Wisconsin Regional Primate Research Center, University of Wisconsin, Madison, WI, USA and The Geriatric Research, Education, and Clinical Center, William S. Middleto ...
Venue:
Computational Statistics & Data Analysis
Year:
2002

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Abstract

Microarrays have emerged as powerful tools allowing investigators to assess the expression of thousands of genes in different tissues and organisms. Statistical treatment of the resulting data remains a substantial challenge. Investigators using microarray expression studies may wish to answer questions about the statistical significance of differences in expression of any of the genes under study, avoiding false positive and false negative results. We have developed a sequence of procedures involving finite mixture modeling and bootstrap inference to address these issues in studies involving many thousands of genes. We illustrate the use of these techniques with a dataset involving calorically restricted mice.