![]() ", " There may be more than one spot and therefore more than one row for each probe.")), " ", " Objects of this class contain one row for each spot. ", " Usually created from an ", list("RGList"), " using ", list("MA.RG"), " or ", list("normalizeWithinArrays"), ". ", " Intensities converted to M-values and A-values, i.e., to with-spot and whole-spot contrasts on the log-scale. ", " A class used to store raw intensities as they are read in from an image analysis output file, This package defines the following data classes. Statistical Applications in Genetics and Molecular Biology, Volume 3, Article 3. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Law, CW, Chen, Y, Shi, W, and Smyth, GK (2014). Limma powers differential expression analyses for RNA-sequencing and microarray studies. Ritchie, ME, Phipson, B, Wu, D, Hu, Y, Law, CW, Shi, W, and Smyth, GK (2015). Robust hyperparameter estimation protects against hypervariable genes and improves power to detect differential expression.Īnnals of Applied Statistics 10, 946-963. Phipson, B, Lee, S, Majewski, IJ, Alexander, WS, and Smyth, GK (2016). Gordon Smyth, with contributions from many colleagues The function changeLog displays the record of changes to the package. The LIMMA contents page gives an alphabetical index of detailed help topics. list()Īn overview of limma functions grouped by purpose is contained in the numbered chapters at the foot of the LIMMA package index page, of which this page is the first. The function limmaUsersGuide gives the file location of the User's Guide. The list("LIMMA User's Guide") can be reached through the "User Guides and Package Vignettes" links at the top of the LIMMA contents page. There are three types of documentation available: The linear model and differential expression functions apply to all gene expression technologies, including microarrays, RNA-seq and quantitative PCR. LIMMA provides the ability to analyse comparisons between many RNA targets simultaneously in arbitrary complicated designed experiments.Įmpirical Bayesian methods are used to provide stable results even when the number of arrays is small. LIMMA is a library for the analysis of gene expression microarray data, especially the use of linear models for analysing designed experiments and the assessment of differential expression.
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