For getting started, we recommend Scanpy’s reimplementation of Seurat’s [Satija15] clustering tutorial for 3K PBMCs from 10x Genomics, containing preprocessing, clustering and the identification of cell types via known marker genes.

For more possibilities on visualizing marker genes, see this plotting gallery.

Trajectory Inference

For trajectory inference on complex datasets, we offer several examples here. Get started here for the following result on hematopoiesis.

You can extend this to multi-resolution analyses of whole animals, such as here.

The PAGA method behind this is described in [Wolf19]. As a reference for simple pseudotime analyses, we provide the diffusion pseudotime analyses of [Haghverdi16] for two hematopoiesis datasets: here for [Paul15] and here for [Moignard15].

Further Tutorials

Conversion: AnnData, SingleCellExperiment, and Seurat objects

See this notebook for a tutorial on anndata2ri.

Regressing out cell cycle

See this notebook.

Scaling Computations

Visualize and cluster 1.3M neurons from 10x Genomics here.


Simulating single cells using literature-curated gene regulatory networks [Wittmann09].


See a pseudotime-based vs. deep-learning based reconstruction of cell cycle from image data here [Eulenberg17].