title: Gene selection with the δ-sequence method.
abstract: In this chapter, we discuss a method of selecting differentially expressed genes based on a newly discovered structure termed as the δ-sequence. Together with the nonparametric empirical Bayes methodology, it leads to dramatic gains in terms of the mean numbers of true and false discoveries, and in the stability of the results of testing. Furthermore, its outcomes are entirely free from the log-additive array-specific technical noise. The new paradigm offers considerable scope for future developments in this area of methodological research.
authors: Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA. xing.qiu@gmail.com
authors: Xing
authors: X
authors: Qiu
authors: Lev
authors: L
authors: Klebanov
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D016012:Poisson Distribution; D025341:Principal Component Analysis; D018709:Statistics, Nonparametric