A robust ratio estimator of gene expression via inverse-variance weighting for cDNA microarray images

In microarray processing, the appearance of artifacts, donuts, and irregularly shaped spots is a problem. In current microarray analysis, most approaches stress the segmentation of pixel intensities rather than emphasizing ratio estimators. To avoid segmenting spot target areas and to minimize sensitivity to aberrant pixels, we propose a robust ratio estimator of gene expression via inverse-variance weighting. Moreover, a metric is proposed to evaluate the spot quality. Both the simulation and numerical examples explored reveal that the proposed algorithm is superior to existing approaches with respect to mean square error. The acceptance quality measure recommended confirms the validity of the proposed ratio estimator.