STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data

Massimo Andreatta; Santiago J Carmona

doi:10.1093/bioinformatics/btaa755

STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data

Bioinformatics. 2021 May 5;37(6):882-884. doi: 10.1093/bioinformatics/btaa755.

Authors

Massimo Andreatta^{1

2

3}, Santiago J Carmona^{1

2

3}

Affiliations

¹ Ludwig Institute for Cancer Research Lausanne, University of Lausanne, CH-1066 Epalinges, Switzerland.
² Department of Oncology, CHUV, UNIL CHUV, CH-1066 Epalinges, Lausanne, Switzerland.
³ University of Lausanne, Lausanne, Switzerland.

Abstract

Summary: STACAS is a computational method for the identification of integration anchors in the Seurat environment, optimized for the integration of single-cell (sc) RNA-seq datasets that share only a subset of cell types. We demonstrate that by (i) correcting batch effects while preserving relevant biological variability across datasets, (ii) filtering aberrant integration anchors with a quantitative distance measure and (iii) constructing optimal guide trees for integration, STACAS can accurately align scRNA-seq datasets composed of only partially overlapping cell populations.

Availability and implementation: Source code and R package available at https://github.com/carmonalab/STACAS; Docker image available at https://hub.docker.com/repository/docker/mandrea1/stacas_demo.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Exome Sequencing
RNA-Seq
Sequence Analysis, RNA
Single-Cell Analysis*
Software*