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Bioinformatics Advance Access originally published online on January 29, 2004
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Bioinformatics 20(6) © Oxford University Press 2004; all rights reserved.

Gene selection for oligonucleotide array: an approach using PM probe level data

Dung-Tsa Chen 1,*, Sue-Hwa Lin 2 and Seng-jaw Soong 1

1 Biostatistics and Bioinformatics Unit, Comprehensive Cancer Center, University of Alabama at Birmingham, 153 Wallace Tumor Institute, 1824 6th Avenue South, Birmingham, AL 35294, USA and 2 Department of Molecular Pathology, University of Texas, M. D. Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030, USA

Received on May 3, 2003 ; revised on July 15, 2003 ; accepted on September 10, 2003
Advance Access Publication January 29, 2004

Motivation: Analysis of oligonucleotide array data, especially to select genes of interest, is a highly challenging task because of the large volume of information and various experimental factors. Moreover, interaction effect (i.e. expression changes depend on probe effects) complicates the analysis because current methods often use an additive model to analyze data. We propose an approach to address these issues with the aim of producing a more reliable selection of differentially expressed genes. The approach uses the rank for normalization, employs the percentile-range to measure expression variation, and applies various filters to monitor expression changes.

Results: We compare our approach with MAS and Dchip models. A data set from an angiogenesis study is used for illustration. Results show that our approach performs better than other methods either in identification of the positive control gene or in PCR confirmatory tests. In addition, the invariant set of genes in our approach provides an efficient way for normalization.

Contact: dtchen{at}uab.edu

* To whom correspondence should be addressed.


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Oligonucleotide arrays: information from replication and spatial structure
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D.-T. Chen, J. J. Chen, and S.-j. Soong
Probe rank approaches for gene selection in oligonucleotide arrays with a small number of replicates
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[Abstract] [Full Text] [PDF]


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