Journal article
STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data.
- Andreatta M Ludwig Institute for Cancer Research, Lausanne Branch; and Department of Oncology, CHUV; and University of Lausanne, Epalinges, 1066, Switzerland.
- Carmona SJ Ludwig Institute for Cancer Research, Lausanne Branch; and Department of Oncology, CHUV; and University of Lausanne, Epalinges, 1066, Switzerland.
- 2020-08-27
Published in:
- Bioinformatics (Oxford, England). - 2020
Statistics and Probability
Computational Theory and Mathematics
Biochemistry
Molecular Biology
Computational Mathematics
Computer Science Applications
English
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
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.
SUPPLEMENTARY INFORMATION
Interactive TIL atlas constructed using STACAS: http://tilatlas.unil.ch.
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
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.
SUPPLEMENTARY INFORMATION
Interactive TIL atlas constructed using STACAS: http://tilatlas.unil.ch.
- Language
-
- English
- Open access status
- green
- Identifiers
-
- DOI 10.1093/bioinformatics/btaa755
- PMID 32845323
- Persistent URL
- https://sonar.ch/global/documents/145107
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