Improving microarray expressions with recalibration

Abstract

Due to the nature of microarray experiments, gene expression levels across and through slide channels can experience up to 103 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.