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Bioinformatics Advance Access published online on December 17, 2004
Bioinformatics, doi:10.1093/bioinformatics/bti189
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Received May 21, 2004
Accepted November 11, 2004

Article

Finding differentially expressed genes: pattern generation using Q-values

Osman Abul 1, Reda Alhajj 2*, Faruk Polat 3, and Ken Barker 2

1 Dept of Computer Science, University of Calgary, Calgary, Alberta, Canada; Dept of Computer Engineering, Middle East Technical University, Ankara, Turkey
2 Dept of Computer Science, University of Calgary, Calgary, Alberta, Canada
3 Dept of Computer Engineering, Middle East Technical University, Ankara, Turkey

* To whom correspondence should be addressed.
Reda Alhajj, E-mail: alhajj{at}cpsc.ucalgary.ca


  Abstract

Motivation: It is important to consider finding differentially expressed genes in a dataset of microarray experiments for pattern generation.

Results: We developed two methods which are mainly based on the q-values approach; the first is a direct extension of the q-values approach, while the second uses two approaches: q-values and maximum-likelihood. We present two algorithms for the second method, one for error minimization and the other for confidence bounding. Also, we show how the method called Patterns from Gene Expression (PaGE) [7] can benefit from q-values. Finally, we conducted some experiments to demonstrate the effectiveness of the proposed methods; experimental results on a selected dataset (BRCA1 vs BRCA2 tumor types) are provided.

Abul et al. (2004) Finding differentially expressed genes: pattern generation using Q-values. Symposium on Applied Computing, Proceedings of the 2004 ACM symposium on Applied computing, 138-142; http://doi.acm.org/10.1145/967900.967930

Copyright 2004 Association for Computing Machinery, Inc. Reprinted by permission. Direct permission requests to permissions@acm.org


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