📄 中文摘要
该教程构建了一个完整的单细胞 RNA 测序分析管道，使用 Scanpy 进行数据处理。首先安装所需的库并加载 PBMC 3k 数据集，接着进行质量控制、过滤和归一化，以准备后续分析。随后识别高变基因，进行主成分分析（PCA）以实现降维，并构建聚类可视化。最后，进行细胞类型注释，为单细胞 RNA 测序数据提供全面的分析框架。
使用 Scanpy 构建完整单细胞 RNA 测序分析管道的编码指南：聚类可视化与细胞类型注释
📄 English Summary
A Coding Guide to Build a Complete Single Cell RNA Sequencing Analysis Pipeline Using Scanpy for Clustering Visualization and Cell Type Annotation
This tutorial builds a complete pipeline for single-cell RNA sequencing analysis using Scanpy. It begins with the installation of required libraries and loading the PBMC 3k dataset, followed by quality control, filtering, and normalization to prepare the data for downstream analysis. The pipeline identifies highly variable genes, performs PCA for dimensionality reduction, and constructs clustering visualizations. Finally, it includes cell type annotation, providing a comprehensive framework for analyzing single-cell RNA sequencing data.