ELB-Q: A new method for improving the robustness in DNA microarray image quantification

Document Type

Article

Publication Date

9-1-2007

Abstract

Reliable and robust quantification of signal intensities is a critical step in microarray-based biomedical studies. However, traditional techniques for microarray image processing would face significant challenges if the number of pixels used for the quantification of the local background and the foreground decreases dramatically. We have developed a new method, ELB-Q, which, by design, is well suited for the image quantification of microarrays with very high density of spot layout (large number of spots arranged in unit area). In ELB-Q, a large extended local background (ELB) interspot region excluding those "noise of the background" pixels is used for estimating the local background, and the quantification of spot intensities (mean and median) in the putative target spot regions is performed after further excluding background pixels in these areas based on the cutoff values established during the ELB calculation. ELB-Q takes advantage of the abundant spatial information around each spot of interest, makes no assumption of the shape and size of the spots, and needs no sophisticated adjustment. We show results of image processing using ELB-Q on both the simulated data and real DNA microarrays, which compare favorably in robustness and accuracy against those obtained with GenePix Pro 6.0 (Axon Instruments, 1999) and the Markov random field (MRF) modeling approach (O. Demirkaya et al., Bioinformatics, vol. 21, pp. 2994-3000, 2005). The ELB-Q software is developed in Matlab, and is available upon request. © 2007 IEEE.

Identifier

34548671868 (Scopus)

Publication Title

IEEE Transactions on Information Technology in Biomedicine

External Full Text Location

https://doi.org/10.1109/TITB.2006.884360

ISSN

10897771

PubMed ID

17912974

First Page

574

Last Page

582

Issue

5

Volume

11

Fund Ref

National Science Foundation

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