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.

中文翻译：

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STACAS：Seurat 中用于比对的亚型锚校正，用于整合单细胞 RNA-seq 数据。

STACAS 是一种用于在 Seurat 环境中识别整合锚点的计算方法，针对仅共享一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)校正批次效应，同时保留跨数据集的相关生物变异性，ii)使用定量距离测量过滤异常的整合锚点，以及iii)构建用于整合的最佳指导树，STACAS 可以准确地对齐仅由以下组成的 scRNA-seq 数据集部分重叠的细胞群。