CytoTalk: De novo construction of signal transduction networks using single-cell transcriptomic data.
CytoTalk: De novo construction of signal transduction networks using single-cell transcriptomic data.
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CytoTalk：利用单细胞转录组数据从头构建信号转导网络
DOI：
10.1126/sciadv.abf1356
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发表时间：
2021-04
期刊：
影响因子：
13.6
通讯作者：
Tan K
中科院分区：
文献类型：
--
作者：
Hu Y;Peng T;Gao L;Tan K
CytoTalk是一种新的计算方法，从单细胞转录组数据推断细胞类型特异性信号网络。单细胞技术使复杂组织中的信号转导研究具有前所未有的分辨率。我们描述CytoTalk从头构建细胞类型特异性信号网络使用单细胞转录组数据。使用一个集成的细胞内和细胞间的基因网络作为输入，CytoTalk使用获奖的施泰纳森林算法识别候选途径。使用高通量的空间转录组数据和单细胞RNA测序数据与受体基因扰动，我们证明了CytoTalk有显着的改进，比现有的算法。为了更好地了解不同组织和发育阶段信号网络的可塑性，我们对人类成人和胎儿组织中巨噬细胞和内皮细胞之间的信号网络进行了比较分析。我们的分析揭示了整个成人组织和特定的网络节点，有助于增加可塑性的信号网络的整体可塑性增加。CytoTalk能够从头构建信号转导通路，并有助于跨组织和条件对这些通路进行比较分析。
CytoTalk is a novel computational method that infers cell type–specific signaling networks from single-cell transcriptomic data. Single-cell technology enables study of signal transduction in a complex tissue at unprecedented resolution. We describe CytoTalk for de novo construction of cell type–specific signaling networks using single-cell transcriptomic data. Using an integrated intracellular and intercellular gene network as the input, CytoTalk identifies candidate pathways using the prize-collecting Steiner forest algorithm. Using high-throughput spatial transcriptomic data and single-cell RNA sequencing data with receptor gene perturbation, we demonstrate that CytoTalk has substantial improvement over existing algorithms. To better understand plasticity of signaling networks across tissues and developmental stages, we perform a comparative analysis of signaling networks between macrophages and endothelial cells across human adult and fetal tissues. Our analysis reveals an overall increased plasticity of signaling networks across adult tissues and specific network nodes that contribute to increased plasticity. CytoTalk enables de novo construction of signal transduction pathways and facilitates comparative analysis of these pathways across tissues and conditions.
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影响因子：
4.4
作者：
Huminiecki L;Lloyd AT;Wolfe KH
通讯作者：
Wolfe KH
T细胞共刺激和共抑制的分子机制。
DOI：
10.1038/nri3405
发表时间：
2013-04
期刊：
Nature reviews. Immunology
影响因子：
--
作者：
通讯作者：
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影响因子：
82.9
作者：
通讯作者：
--
影响因子：
14.9
作者：
Frankish A;Diekhans M;Ferreira AM;Johnson R;Jungreis I;Loveland J;Mudge JM;Sisu C;Wright J;Armstrong J;Barnes I;Berry A;Bignell A;Carbonell Sala S;Chrast J;Cunningham F;Di Domenico T;Donaldson S;Fiddes IT;García Girón C;Gonzalez JM;Grego T;Hardy M;Hourlier T;Hunt T;Izuogu OG;Lagarde J;Martin FJ;Martínez L;Mohanan S;Muir P;Navarro FCP;Parker A;Pei B;Pozo F;Ruffier M;Schmitt BM;Stapleton E;Suner MM;Sycheva I;Uszczynska-Ratajczak B;Xu J;Yates A;Zerbino D;Zhang Y;Aken B;Choudhary JS;Gerstein M;Guigó R;Hubbard TJP;Kellis M;Paten B;Reymond A;Tress ML;Flicek P
通讯作者：
Flicek P
影响因子：
48
作者：
Browaeys, Robin;Saelens, Wouter;Saeys, Yvan
通讯作者：
Saeys, Yvan