Image metrics in the statistical analysis of DNA microarray data

DNA microarrays represent an important new method for determining the compl ete expression profile of a cell. In "spotted" microarrays, slides carrying spots of target DNA are hybridized to fluorescently labeled cDNA from expe rimental and control cells and the arrays are imaged at two or more wavelen gths. In this paper, we perform statistical analysis on images of microarra ys and show that quantitating the amount of fluorescent DNA bound to microa rrays is subject to considerable uncertainty because of large and small-sca le intensity fluctuations within spots, nonadditive background, and fabrica tion artifacts. Pixel-by-pixel analysis of individual spots can be used to estimate these sources of error and establish the precision and accuracy wi th which gene expression ratios are determined. Simple weighting schemes ba sed on these estimates are effective in improving significantly the quality of microarray data as it accumulates in a multiexperiment database. We pro pose that error estimates from image-based metrics should be one component in an explicitly probabilistic scheme for the analysis of DNA microarray da ta.