This course provides a comprehensive introduction to the theoretical foundations and bioinformatics analysis of single‑cell RNA sequencing (scRNA‑seq). It begins with an overview of the technological history (from the first publication in 2009 to spatial transcriptomics in 2020), a comparison of 13 major scRNA‑seq methods, and the current status and challenges of plant single‑cell research. The core principles of the 10X Genomics Chromium platform are then explained in depth, including Gel Bead‑in‑Emulsion (GEM) formation, barcode/UMI tagging, library construction, and the CellRanger quantification pipeline, along with key quality‑control metrics (cell capture rate, gene detection counts, etc.). The basic analysis section centers on the Seurat package, covering data filtering and normalization, highly variable gene selection, PCA dimensionality reduction, UMAP/t‑SNE clustering, cell‑type annotation (using databases such as PlantscRNAdb and known marker genes), and differential expression analysis. Advanced analysis focuses on four major topics: multi‑dataset integration and batch correction (comparison and application scenarios of merge, SCT, Harmony, CCA, and RPCA); cell‑cell communication analysis (PlantPhoneDB database and ligand‑receptor pairs); pseudotime trajectory analysis (Monocle2 inference and gene‑set selection strategies); and copy number variation (inferCNV for inferring tumor heterogeneity). The course emphasizes the specific considerations and available resources for plant single‑cell studies, providing a complete knowledge framework from experimental design to data mining, supporting research in developmental biology, disease mechanisms, and crop improvement.