STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data.
Details
Serval ID
serval:BIB_D3F01C447F08
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data.
Journal
Bioinformatics
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Publication state
Published
Issued date
05/05/2021
Peer-reviewed
Oui
Volume
37
Number
6
Pages
882-884
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Publication Status: ppublish
Abstract
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.
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.
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.
Keywords
RNA-Seq, Sequence Analysis, RNA, Single-Cell Analysis, Software, Whole Exome Sequencing
Pubmed
Web of science
Open Access
Yes
Funding(s)
Swiss National Science Foundation / Projects / 00P3_180010
Create date
10/09/2020 10:18
Last modification date
12/01/2022 7:13