SCENIC: single-cell regulatory network inference and clustering
SCENIC: single-cell regulatory network inference and clustering
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DOI：
10.1038/nmeth.4463
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发表时间：
2017-11-01
期刊：
影响因子：
48
通讯作者：
Aerts, Stein
中科院分区：
文献类型：
--
作者：
Aibar, Sara;Gonzalez-Blas, Carmen Bravo;Aerts, Stein
我们提出了SCENIC，一种从单细胞RNA-seq数据同时重建基因调控网络和识别细胞状态的计算方法（http：scenic.aertslab.org）。在肿瘤和脑的单细胞数据的纲要上，我们证明了顺式调节分析可以用来指导转录因子和细胞状态的鉴定。SCENIC为驱动细胞异质性的机制提供了重要的生物学见解。
We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://scenic.aertslab.org). On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.