Noise factor analysis for cDNA microarrays

Journal of Biomedical Optics
Yoganand BalagurunathanRaymond Carroll

Abstract

A microarray-image model is used that takes into account many factors, including spot morphology, signal strength, background fluorescent noise, and shape and surface degradation. The model yields synthetic images whose appearance and quality reflect that of real microarray images. The model is used to link noise factors to the fidelity of signal extraction with respect to a standard image-extraction algorithm. Of particular interest is the identification of the noise factors and their interactions that significantly degrade the ability to accurately detect the true gene-expression signal. This study uses statistical criteria in conjunction with the simulation of various noise conditions to better understand the noise influence on signal extraction for cDNA microarray images. It proposes a paradigm that is implemented in software. It specifically considers certain kinds of noise in the noise model and sets these at certain levels; however, one can choose other types of noise or use different noise levels. In sum, it develops a statistical package that can work in conjunction with the existing image simulation toolbox.

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Citations

Jun 30, 2007·Bioinformatics·Antonis DaskalakisGeorge Nikiforidis
Feb 4, 2010·IEEE Transactions on Nanobioscience·Leila MureşanGerhard J Schütz
Jul 20, 2006·BMC Bioinformatics·Matti NykterOlli Yli-Harja
Sep 5, 2013·International Journal of Bioinformatics Research and Applications·Huixiao HongLeming Shi
Jul 31, 2009·IET Systems Biology·S Z DenicR Palanivelu
Apr 7, 2010·Journal of Biomedical Informatics·Christos ArgyropoulosGeorge C Sakellaropoulos
Aug 21, 2007·Journal of the American Chemical Society·Thimmaiah GovindarajuNicholas L Abbott

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