Bioinformatics Vol. 19 no. 7 2003
Pages 834-841
© 2003 Oxford University Press
Gene selection and clustering for time-course and dose–response microarray experiments using order-restricted inference
1 Biostatistics Branch
2 Gene Regulation Group, Laboratory
of Molecular Carcinogenesis.
3 NIEHS Microarray Center,
National Institute of Environmental Health Sciences,
Research Triangle Park,
NC 27709, USA.
Received on August 8, 2002
; revised on November 14, 2002
; accepted on November 29, 2002
We propose an algorithm for selecting and clustering genes according to their time-course or dose–response profiles using gene expression data. The proposed algorithm is based on the order-restricted inference methodology developed in statistics. We describe the methodology for time-course experiments although it is applicable to any ordered set of treatments. Candidate temporal profiles are defined in terms of inequalities among mean expression levels at the time points. The proposed algorithm selects genes when they meet a bootstrap-based criterion for statistical significance and assigns each selected gene to the best fitting candidate profile. We illustrate the methodology using data from a cDNA microarray experiment in which a breast cancer cell line was stimulated with estrogen for different time intervals. In this example, our method was able to identify several biologically interesting genes that previous analyses failed to reveal.
Contact: peddada{at}embryo.niehs.nih.gov
* To whom correspondence should be addressed.
Present address: Amgen Inc. Thousand Oaks, CA
91320, USA.
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