Linear Models For Microarray
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limma Linear Models for Microarray and RNA-Seq Data …
www.bioconductor.orgLimma is a package for the analysis of gene expression data arising from microarray or RNA-seq technologies [32]. A core capability is the use of linear models to assess di erential expression in the context of multifactor designed experiments. Limma provides the ability to analyze comparisons between many RNA targets simultaneously.
Sparsity and smoothness via the fused lasso
web.stanford.edumicroarray data in this paper. ... We begin with a standard linear model yi = j xij ... do not produce sparse models. Subset selection does produce sparse models but is not a convex operation; best subsets selection is combinatorial and is not practical for p>30 or so.
Rui Jiang Xuegong Zhang Michael Q. Zhang Editors Basics of ...
courses.cs.ut.eeModels (HMMs). Of course the basics of Markov chains must also be covered. The Metropolis-Hastings algorithm, Monte Carlo Markov chains (MCMC), and Gibbs sampling are carefully presented. Then these ideas find application in the analysis of microarray data. Here the challenging aspects of multiple hypothesis testing