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Bioinformatics Advance Access published online on February 10, 2006
Bioinformatics, 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
Received October 7, 2005
Revised December 13, 2005
Accepted January 30, 2006

Article

A new summarization method for Affymetrix probe level data

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

1 Department of Electrical Engineering and Computer Science, Technische Universität Berlin, 10587 Berlin, Germany

* To whom correspondence should be addressed.
Sepp Hochreiter, E-mail: hochreit{at}cs.tu-berlin.de


  Abstract

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 to 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 vs. wrongly detected (fold change) and correctly detected significantly different expressed genes in two sets of arrays vs. wrongly detected (p-value). Furthermore FARMS is computationally less expensive then RMA, MAS, and MBEI.

Availability: The FARMS R package is available from http://ni.cs.tu-berlin.de/~hochreit/software/farms/farms.html.

Supplementary information: http://ni.cs.tu-berlin.de/~hochreit/papers/farms/supplementary.ps.

Associate Editor: Dmitrij Frishman
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