AnnData
AnnData is a Python package for handling annotated data matrices, storing experimental measurements (X) alongside observation metadata (obs)…
Maintainer FreedomIntelligence · Last updated April 1, 2026
Automated cell type annotation using reference-based methods including CellTypist, scPred, SingleR, and Azimuth for consistent, reproducible cell labeling. Use when automatically annotating cell types using reference datasets.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-single-cell-cell-annotation
Skill Snapshot
Source Doc
Goal: Automatically annotate cell types using a pre-trained or custom CellTypist model.
Approach: Load a reference model, predict cell types with majority voting for cluster-level consensus, and add predictions to AnnData.
"Automatically label my cell types" → Apply a trained classifier to assign cell type identities based on transcriptomic similarity to a reference atlas.
import celltypist
import scanpy as sc
adata = sc.read_h5ad('adata_processed.h5ad')
## Load model
model = celltypist.models.Model.load(model='Immune_All_Low.pkl')
## Predict cell types
predictions = celltypist.annotate(adata, model=model, majority_voting=True)
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