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Local mean normalization of microarray element signal intensities across an array surface: Quality control and correction of spatially systematic artifacts

机译:整个阵列表面微阵列元件信号强度的局部均值归一化:质量控制和空间系统伪像的校正

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摘要

Here we present a methodology for the normalization of element signal intensities to a mean intensity calculated locally across the surface of a DNA microarray. These methods allow the detection and/or correction of spatially systematic artifacts in microarray data. These include artifacts that can be introduced during the robotic printing, hybridization, washing, or imaging of microarrays. Using array element signal intensities alone, this local mean normalization process can correct for such artifacts because they vary across the surface of the array. The local mean normalization can be used for quality control and data correction purposes in the analysis of microarray data. These algorithms assume that array elements are not spatially ordered with regard to sequence or biological function and require that this spatial mapping is identical between the two sets of intensities to be compared. The tool described in this report was developed in the R statistical language and is freely available on the Internet as part of a larger gene expression analysis package. This Web implementation is interactive and user-friendly and allows the easy use of the local mean normalization tool described here, without programming expertise or downloading of additional software.
机译:在这里,我们介绍了一种将元素信号强度归一化为在整个DNA微阵列表面局部计算的平均强度的方法。这些方法允许检测和/或校正微阵列数据中的空间系统伪像。这些包括可以在自动打印,杂交,清洗或微阵列成像期间引入的伪影。仅使用阵列元件信号强度,该局部均值归一化过程就可以校正此类伪影,因为它们在整个阵列表面上都不同。局部均值归一化可用于微阵列数据分析中的质量控制和数据校正目的。这些算法假定数组元素在序列或生物学功能方面不是空间排序的,并且要求在要比较的两组强度之间此空间映射是相同的。本报告中描述的工具是用R统计语言开发的,作为较大的基因表达分析软件包的一部分,可以在Internet上免费使用。此Web实施是交互式且用户友好的,并且允许轻松使用此处描述的本地均值归一化工具,而无需编程专业知识或下载其他软件。

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