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HTS-Net:一种用于在高通量筛选中建立网络调控模型的整合调控组-互作组方法。

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings.

作者信息

Rioualen Claire, Da Costa Quentin, Chetrit Bernard, Charafe-Jauffret Emmanuelle, Ginestier Christophe, Bidaut Ghislain

机构信息

Aix-Marseille Univ, Marseille, France.

Inserm, U1068, Centre de Recherche en Cancérologie de Marseille, Marseille, France.

出版信息

PLoS One. 2017 Sep 26;12(9):e0185400. doi: 10.1371/journal.pone.0185400. eCollection 2017.

Abstract

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2).

摘要

高通量RNA干扰筛选(HTS)能够量化从病毒-宿主相互作用到细胞分化等任何特定功能中每个基因缺失所产生的影响。然而,专门用于RNA干扰分析的功能分析工具的开发却较少。HTS-Net是一个基于网络的分析程序,通过在筛选z分数之上整合转录因子-靶基因相互作用数据(调控组)和蛋白质-蛋白质相互作用网络(相互作用组),来识别高通量筛选中受到影响的基因调控模块。HTS-Net会生成详尽的HTML报告,用于结果导航和探索。HTS-Net是一种用于RNA干扰筛选分析的新流程,正如我们重新分析的三项研究所表明的那样,它通过重新对基因进行优先级排序并将其置于生物学背景中,证明了其性能优于简单的按z分数进行基因排名。可从配套网站http://htsnet.marseille.inserm.fr/获取这三个研究数据集的格式化输入数据、用于测试该系统的源代码和网站。我们还将我们的程序与现有算法(CARD和hotnet2)进行了比较。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29b0/5614607/f622d1043a05/pone.0185400.g001.jpg

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