Practical Quality Assessment of Microarray Data by Simulation of Differential Gene Expression

Authors:
Brian E. Howard;Beate Sick;Steffen Heber
Affiliations:
Bioinformatics Research Center, North Carolina State University, Raleigh, United States;Institute of Data Analysis and Process Design, Zurich University of Applied Science, Winterthur, Switzerland;Bioinformatics Research Center, North Carolina State University, Raleigh, United States and Department of Computer Science, North Carolina State University, Raleigh, United States
Venue:
ISBRA '09 Proceedings of the 5th International Symposium on Bioinformatics Research and Applications
Year:
2009

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Abstract

There are many methods for assessing the quality of microarray data, but little guidance regarding what to do when defective data is identified. Depending on the scientific question asked, discarding flawed data from a small experiment may be detrimental. Here we describe a novel quality assessment method that is designed to identify chips that should be discarded from an experiment. This technique simulates a set of differentially expressed genes and then assesses whether discarding each chip enhances or obscures the recovery of this known set. We compare our method to expert annotations derived using popular quality diagnostics and show, with examples, that the decision to discard a chip depends on the details of the particular experiment.