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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >A ROBUST ALGORITHM FOR RATIO ESTIMATION IN TWO-COLOR MICROARRAY EXPERIMENTS
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A ROBUST ALGORITHM FOR RATIO ESTIMATION IN TWO-COLOR MICROARRAY EXPERIMENTS

机译:双色微阵列实验中的比率估计稳健算法

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摘要

The reliability of the algorithms for ratio estimation in two-color microarray image analysis is very important, as these ratios build up the primary source of information for the subsequent analytical procedures (normalization, clustering, classification, etc). Although various algorithms already exist, there is still a need to develop procedures having higher levels of accuracy and robustness. We present a statistical procedure for the detection and removal of aberrant pixels in two-color microarray images. It is based on a linear regression approach, assuming reasonably high level of correlation between the two color channels. This procedure ensures more robust ratio estimation for the spots in both linear regression and traditional segmentation algorithms. The developed algorithms have been evaluated using simulated artificial images and experimental images of different designs. A demonstration version of the software can be downloaded from http://bioinfo.curie.fr/projects/maia/.
机译:双色微阵列图像分析中比率估计的算法的可靠性非常重要,因为这些比率构建了随后的分析过程的主要信息来源(归一化,聚类,分类等)。 虽然已经存在了各种算法,但仍然需要开发具有更高级别的精度和鲁棒性的过程。 我们提出了一种统计程序,用于检测和去除双色微阵列图像中的异常像素。 它基于线性回归方法,假设两个颜色通道之间的相当高的相关性。 该过程确保线性回归和传统分段算法中的斑点的更稳健比估计。 已经使用模拟人造图像和不同设计的实验图像进行了评估了开发的算法。 可以从http://bioinfo.curie.fr/projects/maia/下载该软件的演示版本。

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