Seurat
Overview
Seurat is an R package and data object for single-cell genomics, developed and maintained by the Satija Lab at the New York Genome Center. It is one of the two most widely used analysis environments for single-cell and spatial transcriptomics, which is the core data type behind brain cell-type atlases and the molecular characterisation of neural tissue. First described in 2015 (Satija et al., Nature Biotechnology), it is the standard choice for this analysis in the R ecosystem. The Seurat object is the central data structure: it stores a cell-by-feature count matrix together with cell metadata, dimensionality reductions, cluster assignments, and multi-modal assay layers in a single in-memory object. Seurat v5 extended support to spatially resolved transcriptomics (Visium, Xenium, MERFISH) and introduced sketch-based analysis for datasets spanning millions of cells. It plays the same role in R that AnnData plays in the Python ecosystem, and the two interconvert through AnnData’s h5ad format.
Connections
- relatedTo: AnnData (Seurat and AnnData are the primary single-cell data objects in R and Python; h5ad is the common exchange format between the two ecosystems)
- implements: Cell Ontology
- implements: UBERON
Resources
- https://satijalab.org/seurat/
- https://github.com/satijalab/seurat
- https://doi.org/10.1038/nbt.3192 (Satija et al. 2015, Nature Biotechnology — original paper)
- https://doi.org/10.1038/s41587-023-01767-y (Hao et al. 2023, Nature Biotechnology — Seurat v5)