Single-cell analysis with Seurat, AnnData, and pyUCell.
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Single-cell RNA in R
Source-backed Draft Static checks
Carry one Seurat object through QC, clustering, MAST markers, sample-level pseudobulk, signatures, trajectories, and coexpression modules.
- Input
- Gene-by-cell raw counts and per-cell metadata with cell and sample IDs.
- Analysis unit
- Cell for QC and cluster markers; sample for condition pseudobulk.
- Outputs
- Seurat object, marker and pseudobulk tables, signatures, trajectories, and modules.
- Key limit
- Cluster markers are not replicate-level condition tests; use pseudobulk for that inference.
Single-cell RNA in Python
Source-backed Draft Static checks
Estimate velocity and fate probabilities, then score network activity with AnnData; scCellFie is optional.
- Input
- AnnData with spliced and unspliced layers, cluster labels, and sample IDs.
- Analysis unit
- Cell.
- Outputs
- Velocity, latent time, fate probabilities, and network activity; optional metabolic tasks.
- Key limit
- Fate results depend on the selected states, kernels, and transition weights.
Gene signature scoring in Python with pyUCell
API reminder Draft Static checks
Score supplied gene signatures from an explicit counts layer, inspect gene coverage, and save cell scores, plots, and AnnData.
- Input
- AnnData with a raw counts layer and supplied gene signatures.
- Analysis unit
- Cell.
- Outputs
- Per-cell scores, signature-gene coverage, plots, and AnnData export.
- Key limit
- Missing signature genes affect score interpretation; scores are not differential tests.