校准
转化(遗传学)
统计
数学
参数统计
对数
计算机科学
生物
遗传学
基因
数学分析
作者
Wolfgang Huber,Anja von Heydebreck,Holger Sültmann,Annemarie Poustka,Martin Vingron
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2002-07-01
卷期号:18 (suppl_1): S96-S104
被引量:2217
标识
DOI:10.1093/bioinformatics/18.suppl_1.s96
摘要
Abstract We introduce a statistical model for microarray gene expression data that comprises data calibration, the quantification of differential expression, and the quantification of measurement error. In particular, we derive a transformation h for intensity measurements, and a difference statistic Δh whose variance is approximately constant along the whole intensity range. This forms a basis for statistical inference from microarray data, and provides a rational data pre-processing strategy for multivariate analyses. For the transformation h, the parametric form h(x)=arsinh(a+bx) is derived from a model of the variance-versus-mean dependence for microarray intensity data, using the method of variance stabilizing transformations. For large intensities, h coincides with the logarithmic transformation, and Δh with the log-ratio. The parameters of h together with those of the calibration between experiments are estimated with a robust variant of maximum-likelihood estimation. We demonstrate our approach on data sets from different experimental platforms, including two-colour cDNA arrays and a series of Affymetrix oligonucleotide arrays. Availability: Software is freely available for academic use as an R package at http://www.dkfz.de/abt0840/whuber Contact: w.huber@dkfz.de
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