STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data.
Bioinformatics
; 37(6): 882-884, 2021 05 05.
Article
in En
| MEDLINE
| ID: mdl-32845323
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.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Software
/
Single-Cell Analysis
Language:
En
Journal:
Bioinformatics
Journal subject:
INFORMATICA MEDICA
Year:
2021
Document type:
Article
Affiliation country:
Switzerland
Publication country:
ENGLAND
/
ESCOCIA
/
GB
/
GREAT BRITAIN
/
INGLATERRA
/
REINO UNIDO
/
SCOTLAND
/
UK
/
UNITED KINGDOM