Microarray image analysis: background estimation using quantile and morphological filters

BMC Bioinformatics
Anders Bengtsson, Henrik Bengtsson

Abstract

In a microarray experiment the difference in expression between genes on the same slide is up to 103 fold or more. At low expression, even a small error in the estimate will have great influence on the final test and reference ratios. In addition to the true spot intensity the scanned signal consists of different kinds of noise referred to as background. In order to assess the true spot intensity background must be subtracted. The standard approach to estimate background intensities is to assume they are equal to the intensity levels between spots. In the literature, morphological opening is suggested to be one of the best methods for estimating background this way. This paper examines fundamental properties of rank and quantile filters, which include morphological filters at the extremes, with focus on their ability to estimate between-spot intensity levels. The bias and variance of these filter estimates are driven by the number of background pixels used and their distributions. A new rank-filter algorithm is implemented and compared to methods available in Spot by CSIRO and GenePix Pro by Axon Instruments. Spot's morphological opening has a mean bias between -47 and -248 compared to a bias between 2 and -2 for the rank filte...Continue Reading

References

Dec 19, 2001·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·D M Rocke, B Durbin
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Citations

Sep 10, 2010·Melanoma Research·Martin GludKrzysztof T Drzewiecki
Oct 5, 2007·IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society·Marc Q MaFrank Y Shih
Jul 1, 2009·Genetics and Molecular Biology·Marcelo F CarazzolleGonçalo A G Pereira

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Software Mentioned

just
Matlab
GenePix Pro
Mathworks
R
MathType
GenePix Pro Spot
Spot
Axon GenePix Pro

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