Aligning Biological Manifolds for Integrated Analysis of Single-Cell Data

To develop optimized methods, benchmarks, and best practices to integrate diverse single-cell datasets and construct a unified atlas.

During this project, the Satija lab designed and implemented an algorithm for the integration of diverse sources of single-cell data. The ability to perform high-resolution integration will enable multiple groups to derive a consistent and reproducible set of cell states across datasets, regardless of the profiling technology. Their tool, Seurat, is freely available, as well as accompanying tutorials and documentation.