A measurement error model for microarray data analysis
A measurement error model for microarray data analysis作者机构：Department of Biological Sciences and Biotechnology Tsinghua University Beijing 100084 China State Key Laboratory of Biomembrane and Membrane Biotechnology Tsinghua University Beijing 100084 China National Engineering Research Center for Beijing Biochip Technology 18 Life Science Parkway Beijing 102206 China
出 版 物：《Progress in Natural Science:Materials International》 (自然科学进展·国际材料(英文))
年 卷 期：2005年第15卷第7期
页 面：614-620页
核心收录：
学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 07[理学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0702[理学-物理学]
基 金：Supported by the Department of Science and Technology of China (Grant No. 2002AA2Z2011)
主 题：microarray measurement error model parameter estimation differentially expressed genes.
摘 要：Microarray technology has been widely used to analyze the gene expression levels by detecting fluorescence intensity in a high throughput fashion. However, since the measurement error produced from various sources in microarray experiments is heterogeneous and too large to be ignored, we propose here a measurement error model for microarray data processing, by which the standard deviation of the measurement error is demonstrated to be linearly increased with fluorescence intensity. A robust algorithm, which estimates the parameters of the measurement error model from a single microarray without replicated spots, is provided. The model and algorithm for estimating of the parameters from a given data set are tested on both the real data set and the simulated data set, and the result has been proven satisfactory. And, combining the measurement error model with traditional Z-test method, a full statistical model has been developed It can significantly improve the statistical inference for identifying differentially expressed genes.
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