The core of MOFA is implemented in the Python package mofapy2, but we recommend to use the R package MOFA2 which provides an interface to train a MOFA model with R and run the downstream analysis and takes care of setting up all python dependencies. Alternatively, if you prefer to use Python the package mofax can be used for downstream analysis in Python, see also our FAQ section.

Stable release (easiest)

You can install the stable release from Bioconductor (link):

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


This uses basilisk to automatically set up a Python environment and install all required dependencies.

Developmental version

To use the latest features of MOFA you can install the software from GitHub:

devtools::install_github("bioFAM/MOFA2", build_opts = c("--no-resave-data --no-build-vignettes"))

If you do so, you have to manually install the Python dependencies using pip (from the Unix terminal). Importantly, this has to be done before the R installation.

pip install mofapy2

In addition, it is very likely that you will have to connect R to Python manually using the reticulate interface (see paragraph below).

Notes on the connection of R to Python

The connection between R and Python is dona via reticulate. Latest version of MOFA2 use basilisk to automatically set up a Python environment and install all required dependencies. Alternatively, you can install the python pacakge mofapy2 manually as described above and specify to use this installation when running MOFA. Note that this sometimes this needs configuration and it is the source of most problems in the MOFA2 R package, specially when you have multiple versions of Python installed. See our FAQ section or reach us if you have issues.

Using MOFA2 with older R versions

We recommend using R (>= 4.0) with MOFA2. If you want to use it with older R versions, you can install MOFA2 as

remotes::install_github("bioFAM/MOFA2", ref = "R36", build_opts = c("--no-resave-data --no-build-vignettes"))

Note, that this is only maintained intermittently and you will need to manually install the python package as described above and possibly configure the reticulate interface.

Installation using Docker image

If you use Docker, you can build an image using the provided Dockerfile:

docker build -t mofa2 .

You will then be able to use R or Python from the container.

docker run -ti --rm -v $DATA_DIRECTORY:/data mofa2 R
#                   ^
#                   |
#                    use `-v` to map a folder on your machine to a container directory

The command above will launch R with MOFA2 and its dependencies installed while mounting $DATA_DIRECTORY to the container.

You can also pull the pre-build image from dockerhub.