run_mofa: Train a MOFA model

In MOFA2: Multi-Omics Factor Analysis v2

Description

Function to train an untrained MOFA object.

Usage

run_mofa(object, outfile = NULL, save_data = TRUE, use_basilisk = FALSE)

Arguments

object	an untrained MOFA object
outfile	output file for the model (.hdf5 format). If NULL, a temporary file is created.
save_data	logical indicating whether to save the training data in the hdf5 file. This is useful for some downstream analysis (mainly functions with the prefix plot_data), but it can take a lot of disk space.
use_basilisk	use basilisk to automatically install a conda environment with mofapy2 and all dependencies? If FALSE (default), you should specify the right python binary when loading R with reticulate::use_python(..., force=TRUE) or the right conda environment with reticulate::use_condaenv(..., force=TRUE).

Details

This function is called once a MOFA object has been prepared (using prepare_mofa) In this step the R package calls the mofapy2 Python package, where model training is performed.
The interface with Python is done with the reticulate package. If you have several versions of Python installed and R is not detecting the correct one, you can change it using reticulate::use_python when loading the R session. Alternatively, you can let us install mofapy2 for you using basilisk if you set use_basilisk to TRUE

Value

a trained MOFA object

Examples

# Load data (in data.frame format)
file <- system.file("extdata", "test_data.RData", package = "MOFA2")
load(file) 

# Create the MOFA object
MOFAmodel <- create_mofa(dt)

# Prepare the MOFA object with default options
MOFAmodel <- prepare_mofa(MOFAmodel)

# Run the MOFA model
## Not run:  MOFAmodel <- run_mofa(MOFAmodel, use_basilisk = TRUE) 

MOFA2 documentation built on Nov. 8, 2020, 7:28 p.m.