single-cell-clustering-and-batch-correction-with-omicverse

The skill presents a coherent, purpose-aligned workflow for single-cell clustering and batch integration using omicverse. It relies on established data science steps (QC, HVG, PCA, neighbors, multiple clustering strategies, and batch correction) and confines data movement to local AnnData objects and disk I/O. There are no suspicious download/execution patterns, credential requirements, or data-exfiltration paths. Overall, the footprint is proportionate to its stated tutorial/guide purpose with moderate security risk stemming from complex data handling, but no active risk indicators beyond standard data-science workflows.