scRNA-seq Data Visualization Methods

Visualizing single-cell RNA-seq (scRNA-seq) data is crucial for understanding the complex patterns and relationships within cellular populations. Effective visualization techniques help in identifying clusters, discovering new cell types, and interpreting differential expression results. We have already explored some visualization methods in the basic scRNA-seq data analysis workflow tutorials. For a deeper dive into various visualization techniques, you can follow the tutorials below.

Seurat

Analysis, visualization, and integration of Visium HD spatial datasets with Seurat

scanpy

Core plotting functions — scanpy-tutorials 0.1.dev50+g203afb9 documentation