“ Decoding Mammalian Gene Regulatory Programs through Efficient Microarray , ChIP - chip and Sequence Analysis ”

نویسنده

  • Hongkai Ji
چکیده

An empirical hierarchical Bayes approach was first proposed to analyze gene expression data collected from microarray experiments. Through a closed-form variance shrinkage estimator, information from multiple genes is pooled to increase the statistical power of multiple hypothesis testing. The approach also allows various types of subject matter knowledge to be incorporated conveniently. Caveats in controlling false discovery rate (FDR) will be discussed. When variance shrinkage estimator is employed, inappropriate use of permutations may result in underestimation of FDR.

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تاریخ انتشار 2007