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MOFA2

This is the development version of MOFA2; for the stable release version, see MOFA2.

Multi-Omics Factor Analysis v2


Bioconductor version: Development (3.19)

The MOFA2 package contains a collection of tools for training and analysing multi-omic factor analysis (MOFA). MOFA is a probabilistic factor model that aims to identify principal axes of variation from data sets that can comprise multiple omic layers and/or groups of samples. Additional time or space information on the samples can be incorporated using the MEFISTO framework, which is part of MOFA2. Downstream analysis functions to inspect molecular features underlying each factor, vizualisation, imputation etc are available.

Author: Ricard Argelaguet [aut, cre] , Damien Arnol [aut] , Danila Bredikhin [aut] , Britta Velten [aut]

Maintainer: Ricard Argelaguet <ricard.argelaguet at gmail.com>

Citation (from within R, enter citation("MOFA2")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("MOFA2")

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

Documentation

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

browseVignettes("MOFA2")
Downstream analysis: Overview HTML R Script
MEFISTO on simulated data (temporal) HTML R Script
MOFA2: How to train a model in R HTML R Script
Reference Manual PDF
LICENSE Text

Details

biocViews Bayesian, DimensionReduction, Software, Visualization
Version 1.13.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License file LICENSE
Depends R (>= 4.0)
Imports rhdf5, dplyr, tidyr, reshape2, pheatmap, ggplot2, methods, RColorBrewer, cowplot, ggrepel, reticulate, HDF5Array, grDevices, stats, magrittr, forcats, utils, corrplot, DelayedArray, Rtsne, uwot, basilisk, stringi
System Requirements Python (>=3), numpy, pandas, h5py, scipy, argparse, sklearn, mofapy2
URL https://biofam.github.io/MOFA2/index.html
Bug Reports https://github.com/bioFAM/MOFA2
See More
Suggests knitr, testthat, Seurat, SeuratObject, ggpubr, foreach, psych, MultiAssayExperiment, SummarizedExperiment, SingleCellExperiment, ggrastr, mvtnorm, GGally, rmarkdown, data.table, tidyverse, BiocStyle, Matrix, markdown
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package MOFA2_1.13.0.tar.gz
Windows Binary MOFA2_1.13.0.zip
macOS Binary (x86_64) MOFA2_1.13.0.tgz
macOS Binary (arm64) MOFA2_1.13.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/MOFA2
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MOFA2
Bioc Package Browser https://code.bioconductor.org/browse/MOFA2/
Package Short Url https://bioconductor.org/packages/MOFA2/
Package Downloads Report Download Stats