STACAS is a method for scRNA-seq integration. It is based on the Seurat integration framework, but adds important innovations:
- anchors are down-weighted based on their distance in reciprocal PCA space
- integration trees are constructed based on the 'centrality' of datasets, as measured by the sum of their re-weighted anchor scores
- cell type labels, if known, can be given as input to the algorithm to perform semi-supervised integration
In this demo we will show the application of STACAS to integrate a collection of human immune cell datasets.
See also how STACAS compares to other integration methods, and how it avoids overcorrecting batch effects for heterogeneous data sets, at this demo for T cell data integration
Copy this repository to your local system:
git clone https://github.com/carmonalab/STACAS.demo
Then move to the STACAS.demo folder and open the STACAS.demo.Rproj in RStudio. In this enviroment, you can follow step-by-step the commands outlined in STACAS.demo.Rmd
For installation and documentation on the STACAS package refer to the STACAS Github repository
Massimo Andreatta, Santiago J Carmona, STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data, Bioinformatics, 2020, btaa755, https://doi.org/10.1093/bioinformatics/btaa755