MOFA2

DOI: 10.18129/B9.bioc.MOFA2    

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

Multi-Omics Factor Analysis v2

Bioconductor version: Development (3.16)

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] , Damien Arnol [aut] , Danila Bredikhin [aut] , Britta Velten [aut, cre]

Maintainer: Britta Velten <britta.velten at gmail.com>

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

Installation

To install this package, start R (version "4.2") 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

PDF   Reference Manual

Details

biocViews Bayesian, DimensionReduction, Software, Visualization
Version 1.7.2
In Bioconductor since BioC 3.12 (R-4.0) (2 years)
License LGPL-3.0
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
LinkingTo
Suggests knitr, testthat, Seurat, ggpubr, foreach, psych, MultiAssayExperiment, SummarizedExperiment, SingleCellExperiment, ggrastr, mvtnorm, GGally, rmarkdown, data.table, tidyverse, BiocStyle, Matrix, markdown
SystemRequirements Python (>=3), numpy, pandas, h5py, scipy, argparse, sklearn, mofapy2
Enhances
URL https://biofam.github.io/MOFA2/index.html
BugReports https://github.com/bioFAM/MOFA2
Depends On Me
Imports Me
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Build Report  

Package Archives

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

Source Package
Windows Binary MOFA2_1.7.2.zip (64-bit only)
macOS Binary (x86_64) MOFA2_1.7.2.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/MOFA2
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MOFA2
Package Short Url https://bioconductor.org/packages/MOFA2/
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