背景信号在dna微阵列测量转换中的应用。

Suzy Van Sanden, Tomasz Burzykowski
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引用次数: 1

摘要

随着微阵列应用领域的发展,对适当的统计工具来分析信号强度测量的需求也在增加。为了使来自不同信道和阵列的信号具有可比性,需要进行归一化程序。一个目标,也是本报告的重点,是消除在对数比与两个通道的平均对数强度值的图上看到的曲率。已有许多方法基于两个通道测量之间的偏移假设。在本文中,我们探讨了使用背景测量来估计和纠正偏移。我们将我们的建议与一些众所周知的方法进行比较,将它们应用于两项研究中的微阵列。这两项研究探讨了蔬菜饮食对小鼠结肠和肺组织基因表达的影响。图形插图和健壮的汇总统计表明,所有转换都是对原始数据的改进。总的来说,在考虑了背景测量的情况下,我们提出的变换得到了最好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The use of background signal in the transformation of cDNA-microarray measurements.

As the application field of microarrays grows, so does the need for appropriate statistical tools to analyse the signal intensity measurements. Normalisation procedures are required to make the signals from different channels and arrays comparable. One objective, which is also the focus of this report, is to remove the curvature seen on plots of the log ratio versus the mean log intensity values of two channels.A number of methods already exist that are based on the assumption of a shift between the measurements of the two channels. In this article, we explore the use of background measurements to estimate and correct for the shift. We compare our proposal with some well known methods by applying them to microarrays from two studies. These two studies investigate the effect of vegetable diets on the gene expression in colon and lung tissue of mice. Graphical illustrations and a robust summary statistic show that all transformations are an improvement to the raw data. Overall, the best results are obtained with our proposed transformation that takes the background measurements into account.

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