Screening for changes in gene expression across biological conditions using high throughput technologies is now common in biology. In this paper we present a broad Bayesian multilevel framework for developing computationally fast shrinkage-based screening tools for this purpose. Our scheme makes it easy to adapt the choice of statistics to the goals of the analysis and to the genomic distributions of signal and noise. We empirically investigate the extent to which these shrinkage-based statistics improve performance, and the situations in which such improvements are larger. Our evaluation uses both extensive simulations and controlled biological experiments. The experimental data include a socalled spike-in experiment, in which the target biological signal is known, and a two-sample experiment, which illustrates the typical conditions in which the methods are applied. Screening for Differentially Expressed Genes: Are Multilevel Models Helpful?: Dongmei Liu, Giovanni Parmigiani and Brian Caffo. OMICS Group through its Open Access Initiative is committed to make genuine and reliable contributions to the scientific community. OMICS Group hosts over 700+ peer-reviewed journals and has organized over 3000+ International Scientific Conferences all over the world. OMICS International is has wide classification of journals and Molecular Biology is one of the important of them. Molecular Biology covers each and every aspect of gene studies from the very basic to the new advance.
Last date updated on August, 2020