Cell Type Annotation

Overview

This pipeline skill generates code for annotating cell types in single-cell RNA-seq data. It covers four complementary approaches:

1. Automated — CellTypist (logistic-regression classifiers trained on curated atlases).
2. Reference-based — SingleR (R) or scANVI/sc.tl.ingest (Python) label transfer.
3. Marker-based — Manual assignment from canonical marker gene panels.
4. Hierarchical — Coarse compartment assignment followed by specialized fine-grained annotation.

Use it when the user has a clustered AnnData (or SingleCellExperiment) and needs cell-type labels in adata.obs.

Usage

Decision Tree: Choosing an Annotation Approach

Follow this decision tree to select the right method: