Image metrics in the statistical analysis of DNA microarray data
Image metrics in the statistical analysis of DNA microarray data
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DOI：
10.1073/pnas.161242998
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发表时间：
2001-07-31
影响因子：
11.1
通讯作者：
Sorger, PK
中科院分区：
文献类型：
--
作者：
Brown, CS;Goodwin, PC;Sorger, PK
DNA 微阵列代表了一种确定细胞完整表达谱的重要新方法。在“点状”微阵列中，载有靶DNA点的载玻片与来自实验细胞和对照细胞的荧光标记的cDNA杂交，并且阵列在两个或多个波长下成像。在本文中，我们对微阵列图像进行统计分析，结果表明，由于点内大大小小的强度波动、非加性背景和制造伪影，定量与微阵列结合的荧光 DNA 的量存在相当大的不确定性。对各个点的逐像素分析可用于估计这些误差源，并确定确定基因表达比率的精度和准确度。当微阵列数据在多实验数据库中积累时，基于这些估计的简单加权方案可有效显着提高微阵列数据的质量。我们建议，基于图像的指标的误差估计应该成为 DNA 微阵列数据分析的显式概率方案的组成部分。
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.