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Laplace Mixture Model in Microarray Experiments

Bioconductor version: Release (3.18)

Laplace mixture modelling of microarray experiments. A hierarchical Bayesian approach is used, and the hyperparameters are estimated using empirical Bayes. The main purpose is to identify differentially expressed genes.

Author: Yann Ruffieux, contributions from Debjani Bhowmick, Anthony C. Davison, and Darlene R. Goldstein

Maintainer: Yann Ruffieux <yann.ruffieux at epfl.ch>

Citation (from within R, enter citation("lapmix")):


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

lapmix example PDF R Script
Reference Manual PDF


biocViews DifferentialExpression, Microarray, OneChannel, Software
Version 1.68.0
In Bioconductor since BioC 1.9 (R-2.4) (17.5 years)
License GPL (>= 2)
Depends R (>= 2.6.0), stats
Imports Biobase, graphics, grDevices, methods, stats, tools, utils
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URL http://www.r-project.org http://www.bioconductor.org http://stat.epfl.ch
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Source Package lapmix_1.68.0.tar.gz
Windows Binary lapmix_1.68.0.zip
macOS Binary (x86_64) lapmix_1.68.0.tgz
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Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/lapmix
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