Scanpy outputs

You receive a processed AnnData file with UMAP embeddings, cluster assignments, and per-cluster marker genes, plus publication-ready figures. These let you annotate cell types from the top markers, feed the .h5ad into scvi-tools for probabilistic modeling, and identify which cell types express a target of interest.

Output files

What you receive

• Processed AnnData: .h5ad file with all computed embeddings and clusters
• UMAP coordinates: CSV with cell embeddings
• Cluster assignments: Cell-to-cluster mapping table
• Marker genes: Top differentially expressed genes per cluster
• Figures: Publication-ready UMAP and violin plots

Interpreting results

UMAP visualization

• Each point represents a cell
• Colors indicate cluster assignment
• Proximity suggests transcriptional similarity

Marker genes

• Ranked by log fold change and adjusted p-value
• Use top markers to annotate cell types
• Cross-reference with known cell type markers

Export formats

• CSV: Tabular data for downstream analysis
• H5AD: Full AnnData for scvi-tools or other Python tools
• PNG/SVG: Figures for publications

Canvas Visualization

When a Scanpy job completes, a result card appears on the canvas.

• Card size: 450x350px
• Border color: Brown (#795548)
• Visualization: UMAP/t-SNE dimensionality reduction plots with cluster coloring

Tier 2 Metrics

• Cell count
• Gene count
• Cluster count
• Median gene count per cell

QC Thresholds

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