Joint analysis of heterogeneous single-cell RNA-seq dataset collections
Joint analysis of heterogeneous single-cell RNA-seq dataset collections
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DOI：
10.1038/s41592-019-0466-z
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发表时间：
2019-08-01
期刊：
影响因子：
48
通讯作者：
Kharchenko, Peter V.
中科院分区：
文献类型：
--
作者：
Barkas, Nikolas;Petukhov, Viktor;Kharchenko, Peter V.
单细胞RNA测序通常应用于包括多个个体、条件或组织的研究设计中。为了在这种异质性集合中识别反复出现的细胞亚群，我们开发了Conos方法，该方法依靠多种合理的样本间映射来构建一个连接所有测量细胞的全局图。该图能够识别反复出现的细胞簇，并在多样本或图谱规模的集合中的数据集之间传播信息。
Single-cell RNA sequencing is often applied in study designs that include multiple individuals, conditions or tissues. To identify recurrent cell subpopulations in such heterogeneous collections, we developed Conos, an approach that relies on multiple plausible inter-sample mappings to construct a global graph connecting all measured cells. The graph enables identification of recurrent cell clusters and propagation of information between datasets in multi-sample or atlas-scale collections.