sumo_setup_mofa

Interactive setup for Python 'mofapy2' via reticulate (fallback when basilisk is unavailable)

Provides tools to simulate multi-omics datasets with predefined signal structures. The generated data can be used for testing, validating, and benchmarking integrative analysis methods such as factor models and clustering approaches. This version includes enhanced signal customization, visualization tools (scatter, histogram, 3D), MOFA-based analysis pipelines, PowerPoint export, and statistical profiling of datasets. Designed for both method development and teaching, SUMO supports real and synthetic data pipelines with interpretable outputs. Tini, Giulia, et al (2019) <doi:10.1093/bib/bbx167>.

Bernard Isekah Osang'ir

SUMO

Generating Multi-Omics Datasets for Testing and Benchmarking

Ziv Shkedy

Surya Gupta

Jürgen Claesen

sumo_setup_mofa function

<dl><dt>envname</dt>
<dd>Name of the <code>conda</code> environment to create/use.</dd>
<dt>py_version</dt>
<dd>Python version (e.g., "3.10").</dd></dl>

Arguments

Interactive setup for Python 'mofapy2' via reticulate (fallback when basilisk is unavailable) — sumo_setup_mofa

<dl>

<dt>envname</dt>
<dd>Name of the <code>conda</code> environment to create/use.</dd>


<dt>py_version</dt>
<dd>Python version (e.g., "3.10").</dd>

</dl>

sumo_setup_mofa: Interactive setup for Python 'mofapy2' via reticulate (fallback when basilisk is unavailable)

Description

Usage

Value

Arguments