R package lemma: Laplace approximated EM Microarray Analysis. LEMMA is used to detect ”nonnull genes” - genes for which the average response in treatment group 1 is significantly different from the average response in group 2, in normalized microarray data. LEMMA is an implementation of an approximate EM algorithm to estimate the parameters in the assumed linear model in Bar, Booth, Schifano, Wells (2009).
Keywords for this software
References in zbMATH (referenced in 4 articles , 1 standard article )
Showing results 1 to 4 of 4.
- Wang, Chamont; Gevertz, Jana L.: Finding causative genes from high-dimensional data: an appraisal of statistical and machine learning approaches (2016)
- Liu, Peng; Wang, Chong: Robust semiparametric optimal testing procedure for multiple normal means (2012)
- Bar, Haim Y.; Schifano, Elizabeth D.: Empirical and fully Bayesian approaches for random effects models in microarray data analysis (2011)
- Bar, Haim; Booth, James; Schifano, Elizabeth; Wells, Martin T.: Laplace approximated EM microarray analysis: an empirical Bayes approach for comparative microarray experiments (2010)