SC3: consensus clustering of single-cell RNA-seq data
SC3: consensus clustering of single-cell RNA-seq data
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DOI：
10.1038/nmeth.4236
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发表时间：
2017-05-01
期刊：
影响因子：
48
通讯作者：
Hemberg, Martin
中科院分区：
文献类型：
--
作者：
Kiselev, Vladimir Yu;Kirschner, Kristina;Hemberg, Martin
单细胞RNA-seq能够基于全局转录组谱对细胞类型进行定量表征。我们提出了单细胞共识聚类（SC 3），一个用户友好的工具，无监督聚类，实现高准确性和鲁棒性，通过结合多个聚类解决方案，通过共识的方法（http：//bioconductor.org/packages/SC3）。我们证明，SC 3是能够识别从患者收集的肿瘤细胞的转录组的亚克隆。
Single-cell RNA-seq enables the quantitative characterization of cell types based on global transcriptome profiles. We present single-cell consensus clustering (SC3), a user-friendly tool for unsupervised clustering, which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach (http://bioconductor.org/packages/SC3). We demonstrate that SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients.