文章基本信息

标题：Image metrics in the statistical analysis of DNA microarray data
本地全文：下载
作者：Carl S. Brown ; Paul C. Goodwin ; Peter K. Sorger 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2001
卷号：98
期号：16
页码：8944-8949
DOI：10.1073/pnas.161242998
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：DNA microarrays represent an important new method for determining the complete expression profile of a cell. In "spotted" microarrays, slides carrying spots of target DNA are hybridized to fluorescently labeled cDNA from experimental and control cells and the arrays are imaged at two or more wavelengths. In this paper, we perform statistical analysis on images of microarrays and show that quantitating the amount of fluorescent DNA bound to microarrays is subject to considerable uncertainty because of large and small-scale intensity fluctuations within spots, nonadditive background, and fabrication artifacts. Pixel-by-pixel analysis of individual spots can be used to estimate these sources of error and establish the precision and accuracy with which gene expression ratios are determined. Simple weighting schemes based on these estimates are effective in improving significantly the quality of microarray data as it accumulates in a multiexperiment database. We propose that error estimates from image-based metrics should be one component in an explicitly probabilistic scheme for the analysis of DNA microarray data.