Multi-modal Modeling ==================================== MESA Modeling ------------- CFTK includes MESA-style multimodal modeling commands. Install the analysis dependencies, including ``mesa-cfdna``, before using these commands: .. code-block:: bash python -m pip install ".[analysis]" Run modality performance screening: .. code-block:: bash cftk --config cftk_init.json mesa --performance Run model construction: .. code-block:: bash cftk --config cftk_init.json mesa --mesa-model Run leave-one-out cross-validation and plots: .. code-block:: bash cftk --config cftk_init.json mesa --loocv Commonly used together: .. code-block:: bash cftk --config cftk_init.json mesa --performance --mesa-model --loocv Expected Outputs ---------------- MESA writes a compact set of tables, a serialized model, and LOOCV figures: .. code-block:: text results/5_mesa/ |-- label.tsv |-- modality_performance.tsv |-- MESA_model.pkl |-- loocv_predictions.tsv |-- mesa_roc.png / mesa_roc.pdf |-- mesa_heatmap.png / mesa_heatmap.pdf `-- mesa_spearman.png / mesa_spearman.pdf The observed visual below combines those plot families with the prediction table for five controls and five sALS samples. It is a technical workflow example only. In particular, perfect-looking internal screening values can occur in a ten-sample run and do not estimate performance for a cohort or a clinical assay. Inspect ``loocv_predictions.tsv``, the model settings, and the provenance manifest before interpreting any result. .. figure:: ../_static/validation_10sample_mesa.png :alt: Observed MESA screening, LOOCV ROC, aliased predictions, and score correlations for five controls and five sALS samples :width: 100% Observed MESA output from **five controls and five sALS samples**. The internal screening bars and LOOCV curves are descriptive artifacts from this ten-sample technical run, not biological or clinical validation and not a recommended acceptance threshold. Download the sanitized aggregate metadata: :download:`JSON <../_static/validation_10sample_downstream_summary.json>`.