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Bioinformatics Advance Access originally published online on February 10, 2006
Bioinformatics 2006 22(8):943-949; doi:10.1093/bioinformatics/btl033
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A new summarization method for affymetrix probe level data

Sepp Hochreiter *,1,2, Djork-Arné Clevert 1 and Klaus Obermayer 1

1 Department of Electrical Engineering and Computer Science, Technische Universität Berlin 10587 Berlin, Germany
2 Institute of Bioinformatics, Johannes Kepler Universität Linz 4040 Linz, Austria

*To whom correspondence should be adderessed.

Motivation: We propose a new model-based technique for summarizing high-density oligonucleotide array data at probe level for Affymetrix GeneChips. The new summarization method is based on a factor analysis model for which a Bayesian maximum a posteriori method optimizes the model parameters under the assumption of Gaussian measurement noise. Thereafter, the RNA concentration is estimated from the model. In contrast to previous methods our new method called ‘Factor Analysis for Robust Microarray Summarization (FARMS)’ supplies both P-values indicating interesting information and signal intensity values.

Results: We compare FARMS on Affymetrix's spike-in and Gene Logic's dilution data to established algorithms like Affymetrix Microarray Suite (MAS) 5.0, Model Based Expression Index (MBEI), Robust Multi-array Average (RMA). Further, we compared FARMS with 43 other methods via the ‘Affycomp II’ competition. The experimental results show that FARMS with default parameters outperforms previous methods if both sensitivity and specificity are simultaneously considered by the area under the receiver operating curve (AUC). We measured two quantities through the AUC: correctly detected expression changes versus wrongly detected (fold change) and correctly detected significantly different expressed genes in two sets of arrays versus wrongly detected (P-value). Furthermore FARMS is computationally less expensive then RMA, MAS and MBEI.

Availability: The FARMS R package is available from http://www.bioinf.jku.at/software/farms/farms.html

Contact: hochreit{at}bioinf.jku.at

Supplementary information: http://www.bioinf.jku.at/publications/papers/farms/supplementary.ps

Received on October 7, 2005; revised on December 13, 2005; accepted on January 30, 2006

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