Noise filtering and microarray image reconstruction via chained fouriers

Authors:
Karl Fraser;Zidong Wang;Yongmin Li;Paul Kellam;Xiaohui Liu
Affiliations:
School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex, UK;School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex, UK;School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex, UK;Department of Infection, University College London, London, UK;School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex, UK
Venue:
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
Year:
2007

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Abstract

Microarrays allow biologists to determine the gene expressions for tens of thousands of genes simultaneously, however due to biological processes, the resulting microarray slides are permeated with noise. During quantification of the gene expressions, there is a need to remove a gene's noise or background for purposes of precision. This paper presents a novel technique for such a background removal process. The technique uses a gene's neighbour regions as representative background pixels and reconstructs the gene region itself such that the region resembles the local background. With use of this new background image, the gene expressions can be calculated more accurately. Experiments are carried out to test the technique against a mainstream and an alternative microarray analysis method. Our process is shown to reduce variability in the final expression results.