Bioinformatics Advance Access published online on October 5, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm478
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I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data.
1 Johnson & Johnson Pharmaceutical Research & Development, a division of Janssen Pharmaceutica n.v., Beerse, Belgium
2 Institute of Bioinformatics, Johannes Kepler Universität Linz 4040 Linz, Austria
3 Department of Nephrology and Internal Intensive Care, Charité University Medicine, Berlin
4 Johnson & Johnson Pharmaceutical Research & Development, Raritan, US
*To whom correspondence should be addressed. Dr. Willem Talloen, E-mail: wtalloen{at}prdbe.jnj.com
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Abstract |
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Motivation: DNA microarray technology typically generates many measurements of which only a relatively small subset is informative for the interpretation of the experiment. To avoid false positive results, it is therefore critical to select the informative genes from the large noisy data before the actual analysis. Most currently available filtering techniques are supervised and therefore suffer from a potential risk of overfitting. The unsupervised filtering techniques, on the other hand, are either not very efficient or too stringent as they may mix up signal with noise. We propose to use the multiple probes measuring the same target mRNA as repeated measures to quantify the signal-to-noise ratio of that specific probe set. A Bayesian factor analysis with specifically chosen prior settings, that models this probe level information, is providing an objective feature filtering technique, named I/NI calls.
Results: Based on 30 real-life data sets (including various human, rat, mice and Arabidopsis studies) and a spiked-in data set, it is shown that I/NI calls is highly effective, with exclusion rates ranging from 70 to 99%. Consequently, it offers a critical solution to the curse of high-dimensionality in the analysis of microarray data.
Availability: This filtering approach is publicly available as a function implemented in the R package FARMS (www.bioinf.jku.at/software/farms/farms.html).
Abbreviations: Informative/Non-informative calls (I/NI calls), Absent/Present calls (A/P calls), FARMS (Factor Analysis for Robust Microarray Summarization)
Associate Editor: Prof. David Rocke
Both authors contributed equally to this work.
Received on April 13, 2007; revised on September 7, 2007; accepted on September 18, 2007
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