Multiomics Result Result #91 — Analysis Report
Contents
- mofa2 (#91) completed
1. Mofa2
2026-09-21 02:18:34 · multiomics_result
MOFA factor analysis completed across the input views.
mofa variance explained
| View | Factor | R² |
|---|---|---|
| gallery — example_metabolomics.csv | Factor 1 | 0.138522 |
| gallery — example_metabolomics.csv | Factor 2 | 0.0 |
| gallery — example_metabolomics.csv | Factor 3 | 0.027202 |
| gallery — example_proteomics.csv | Factor 1 | 0.000944 |
| gallery — example_proteomics.csv | Factor 2 | 0.0 |
| gallery — example_proteomics.csv | Factor 3 | 0.000339 |
mofa factor scatter
mofa variance bar
Method & Provenance
- Method
- Multi-omics — MOFA2
- Engine
- Python · mofapy2 0.7.5
- Input dataset
- gallery — example_metabolomics.csv
- Started
- 2026-09-21 02:18:34.569473
- Completed
- 2026-09-21 02:18:35.258126
- Permanent link
- https://cat-g-omxpert.wishartlab.com/multiomics/results/by-token/cea42a29cdd8490685f8217ef2055842
| Parameter | Value |
|---|---|
| dataset_ids | — |
| pipeline_type | mofa2 |
Command history
# python from mofapy2.run.entry_point import entry_point # python ent = entry_point() # python ent.set_data_options(scale_views=True) # python ent.set_model_options(factors=10) # python ent.set_train_options(iter=1000, convergence_mode='fast', seed=42) # python ent.build() # python ent.run()