MOFA2
This is the development version of MOFA2; for the stable release version, see MOFA2.
Multi-Omics Factor Analysis v2
Bioconductor version: Development (3.20)
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("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 | ||
LICENSE | Text |
Details
biocViews | Bayesian, DimensionReduction, Software, Visualization |
Version | 1.15.0 |
In Bioconductor since | BioC 3.12 (R-4.0) (4 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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Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | MOFA2_1.15.0.tar.gz |
Windows Binary (x86_64) | MOFA2_1.15.0.zip |
macOS Binary (x86_64) | MOFA2_1.15.0.tgz |
macOS Binary (arm64) | MOFA2_1.15.0.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 |