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Open Access Highly Accessed Research

Sources of nonlinearity in cDNA microarray expression measurements

Latha Ramdas1, Kevin R Coombes23, Keith Baggerly2, Lynne Abruzzo4, W Edward Highsmith5, Tammy Krogmann5, Stanley R Hamilton1 and Wei Zhang1*

Author Affiliations

1 Department of Pathology, University of Texas M D Anderson Cancer Center, Houston, TX 77030, USA

2 Department of Biostatistics, University of Texas M D Anderson Cancer Center, Houston, TX 77030, USA

3 Department of Biomathematics, University of Texas M D Anderson Cancer Center, Houston, TX 77030, USA

4 Department of Hematopathology, Cancer Genomics Core Laboratory, University of Texas M D Anderson Cancer Center, Houston, TX 77030, USA

5 Department of Pathology, University of Maryland, College Park, MD 20742, USA

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Genome Biology 2001, 2:research0047-research0047.7  doi:10.1186/gb-2001-2-11-research0047

Published: 18 October 2001

Abstract

Background

A key assumption in the analysis of microarray data is that the quantified signal intensities are linearly related to the expression levels of the corresponding genes. To test this assumption, we experimentally examined the relationship between signal and expression for the two types of microarrays we most commonly encounter: radioactively labeled cDNAs on nylon membranes and fluorescently labeled cDNAs on glass slides.

Results

We uncovered two sources of nonlinearity. The first, which led to discrepancies in analysis affecting the fluorescent signals, was signal quenching associated with excessive dye concentrations. The second, affecting the radioactive signals, was a nonlinear transformation of the raw data introduced by the scanner. Correction for this transformation was made by some, but not all, image-quantification software packages.

Conclusions

The second type of nonlinearity is more troublesome, because it could not have been predicted a priori. Both types of nonlinearities were detected by simple dilution series, which we recommend as a quality-control step.