[JerryIshihara]

QC metrics implementation and integration:

• Added a new src/cnmf/qc.py module that computes various QC metrics (e.g., pairwise E-distance, clustering metrics, variance explained), saves annotated outputs, and generates heatmap visualizations.
• Integrated the QC step into the consensus workflow by importing and calling run_qc in src/cnmf/cnmf.py, ensuring that QC metrics are calculated and saved after consensus clustering. [1] [2]

Dependency and packaging updates:

• Updated setup.py to include new dependencies required for QC metrics and plotting, specifically seaborn and tqdm.

Testing and reproducibility:

• Added a new test suite tests/test_consensus_qc.py to verify the correctness of E-distance calculations and the full QC output, using synthetic data to ensure results match a known reference implementation. The tests check both the annotation and E-distance outputs, as well as the creation of the heatmap plot.

Tracking

Closes JerryIshihara/sc-blipper#14