scanpy

name	scanpy
description	Scalable toolkit for analyzing single-cell gene expression data. Built on top of Anndata, focusing on clustering, trajectory inference, and visualization.
version	1.9
license	BSD-3-Clause

Scanpy - Single-Cell Analysis

Scanpy processes high-dimensional biological data, reducing it via PCA/UMAP to identify rare cell populations in tissues or microbiomes.

When to Use

• Analyzing single-cell RNA sequencing (scRNA-seq) data.
• Identifying cell types and states in heterogeneous tissues.
• Reconstructing developmental trajectories.
• Comparing cell populations between conditions.
• Discovering rare cell types.

Core Principles

AnnData Format

Scanpy uses AnnData objects that store expression matrix, cell metadata, and gene annotations together.

Dimensionality Reduction

High-dimensional gene expression (20,000+ genes) is reduced to 2D/3D for visualization (PCA → UMAP/t-SNE).

Clustering

Cells are grouped by similarity in gene expression space to identify cell types.

Quick Reference

Standard Imports

import scanpy as sc
import pandas as pd
import numpy  np