Nonparametric Estimation of Genewise Variance for Microarray Data1 By

Abstract

Estimation of genewise variance arises from two important applications in microarray data analysis: selecting significantly differentially expressed genes and validation tests for normalization of microarray data. We approach the problem by introducing a two-way nonparametric model, which is an extension of the famous Neyman–Scott model and is applicable… (More)

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@inproceedings{Fan2010NonparametricEO, title={Nonparametric Estimation of Genewise Variance for Microarray Data1 By}, author={Jianqing Fan and Yang Feng and Yue Niu and Yulong Niu}, year={2010} }