scanpy

Scanpy: Single-Cell Analysis

Overview

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

In the bundled Vibe-Skills routing surface, this skill also absorbs the former AnnData and scVI/scANVI route surfaces. Use it for h5ad container handling and scverse latent-model planning when those tasks appear inside a single-cell workflow.

When to Use This Skill

This skill should be used when:

• Analyzing single-cell RNA-seq data (.h5ad, 10X, CSV formats)
• Performing quality control on scRNA-seq datasets
• Creating UMAP, t-SNE, or PCA visualizations
• Identifying cell clusters and finding marker genes
• Annotating cell types based on gene expression
• Conducting trajectory inference or pseudotime analysis
• Generating publication-quality single-cell plots
• Reading, writing, subsetting, or annotating AnnData/h5ad objects as part of single-cell work
• Planning scVI/scANVI batch-correction, latent-model, or cell-type annotation workflows

Quick Start

Basic Import and Setup

import scanpy as sc
import pandas as pd
import numpy as np

# Configure settings
sc.settings.verbosity = 3
sc.settings.set_figure_params(dpi=80, facecolor='white')
sc.settings.figdir = './figures/'

Loading Data

# From 10X Genomics
adata = sc.read_10x_mtx('path/to/data/')
adata = sc.read_10x_h5('path/to/data.h5')

# From h5ad (AnnData format)
adata = sc.read_h5ad('path/to/data.h5ad')

# From CSV
adata = sc.read_csv('path/to/data.csv')

Understanding AnnData Structure

The AnnData object is the core data structure in scanpy:

adata.X          # Expression matrix (cells × genes)
adata.obs        # Cell metadata (DataFrame)
adata.var        # Gene metadata (DataFrame)
adata.uns        # Unstructured annotations (dict)
adata.obsm       # Multi-dimensional cell data (PCA, UMAP)
adata.raw        # Raw data backup

# Access cell and gene names
adata.obs_names  # Cell barcodes
adata.var_names  # Gene names