scRNA-seq Pipeline (Scanpy)

Overview

This skill produces a reproducible scRNA-seq analysis in Python using Scanpy and AnnData. It covers the standard workflow: load counts → QC filter → normalize/log → HVG → scale/PCA → neighbors/UMAP → Leiden → differential expression, plus batch correction with Harmony or scVI. Default parameters follow the Scanpy PBMC3k tutorial conventions and are safe starting points for most 10X Genomics datasets.

Output is a single .h5ad file with all intermediate embeddings, cluster labels, and DE results stored on the AnnData object.

Usage

Install dependencies:

pip install "scanpy>=1.10" anndata leidenalg python-igraph harmonypy scvi-tools

Run the pipeline end-to-end: