STACAS：在 Seurat 中进行亚型锚定校正以整合单细胞 RNA-seq 数据。
STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data.
机构信息
Ludwig Institute for Cancer Research Lausanne, University of Lausanne, CH-1066 Epalinges, Switzerland.
Department of Oncology, CHUV, UNIL CHUV, CH-1066 Epalinges, Lausanne, Switzerland.
出版信息
Bioinformatics. 2021 May 5;37(6):882-884. doi: 10.1093/bioinformatics/btaa755.
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.
摘要
STACAS 是一种在 Seurat 环境中识别整合锚点的计算方法，针对仅共享部分细胞类型的单细胞（sc）RNA-seq 数据集的整合进行了优化。我们证明，通过（i）在跨数据集保留相关生物学变异性的同时纠正批次效应，（ii）使用定量距离度量筛选异常整合锚点，以及（iii）构建用于整合的最优引导树，STACAS 可以准确地对齐仅由部分重叠细胞群组成的 scRNA-seq 数据集。
可用性和实现
源代码和 R 包可在 https://github.com/carmonalab/STACAS 上获得；Docker 镜像可在 https://hub.docker.com/repository/docker/mandrea1/stacas_demo 上获得。
Zotero 插件