Due to the nature of microarray experiments, gene expression levels across and through slide channels can experience up to fold change differences in intensity. Such data variance is caused by ‘noise’ elements, which can influence final expressions. This paper proposes a simple technique whereby histogram transformations are used to reduce noise artefacts. Akin to a magic eraser (removing the top layer of a surface), the technique attempts to blend pixels associated with gene spots into their background. The identification of pixels is relatively straightforward, but blending them with appropriate values is non‐trivial. Once replacement values are determined, the background should be a good approximation of the original. By subtracting this surface from the original, gene spot regions would be more accurate. Experiments were carried out and results compared to “GenePix” a mainstream microarray process and “O'Neill” a microarray specific reconstruction algorithm. Not only was our process shown to be significantly quicker in execution time, it also reduced final expression results while typically generating less variation within gene's.
Skip Nav Destination
Article navigation
18 September 2007
COMPLIFE 2007: The Third International Symposium on Computational Life Science
4–5 October 2007
Utrecht (The Netherlands)
Research Article|
September 18 2007
Improving Microarray Expressions with Recalibration
Karl Fraser;
Karl Fraser
aSchool of Information Systems, Computing, and Mathematics Brunel University, Uxbridge, Middlesex, UB8 3PH, U.K.
Search for other works by this author on:
Zidong Wang;
Zidong Wang
aSchool of Information Systems, Computing, and Mathematics Brunel University, Uxbridge, Middlesex, UB8 3PH, U.K.
Search for other works by this author on:
Yongmin Li;
Yongmin Li
aSchool of Information Systems, Computing, and Mathematics Brunel University, Uxbridge, Middlesex, UB8 3PH, U.K.
Search for other works by this author on:
Paul Kellam;
Paul Kellam
bDepartment of Infection University College London, London, W1T 4JF, U.K.
Search for other works by this author on:
Xiaohui Liu
Xiaohui Liu
aSchool of Information Systems, Computing, and Mathematics Brunel University, Uxbridge, Middlesex, UB8 3PH, U.K.
Search for other works by this author on:
AIP Conf. Proc. 940, 3–15 (2007)
Citation
Karl Fraser, Zidong Wang, Yongmin Li, Paul Kellam, Xiaohui Liu; Improving Microarray Expressions with Recalibration. AIP Conf. Proc. 18 September 2007; 940 (1): 3–15. https://doi.org/10.1063/1.2793403
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Citing articles via
Inkjet- and flextrail-printing of silicon polymer-based inks for local passivating contacts
Zohreh Kiaee, Andreas Lösel, et al.
Effect of coupling agent type on the self-cleaning and anti-reflective behaviour of advance nanocoating for PV panels application
Taha Tareq Mohammed, Hadia Kadhim Judran, et al.
Design of a 100 MW solar power plant on wetland in Bangladesh
Apu Kowsar, Sumon Chandra Debnath, et al.
Related Content
Automated cDNA Microarray Image Segmentation
AIP Conference Proceedings (November 2007)
Clustering Short Time‐Series Microarray
AIP Conference Proceedings (January 2008)
Shrinkage covariance matrix approach for microarray data
AIP Conference Proceedings (April 2013)
Fuzzy support vector machine for microarray imbalanced data classification
AIP Conference Proceedings (November 2017)
A study of metaheuristic algorithms for high dimensional feature selection on microarray data
AIP Conference Proceedings (November 2017)