enrichMiR predicts functionally relevant microRNAs based on target collections.
enrichMiR predicts functionally relevant microRNAs based on target collections.
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DOI：
10.1093/nar/gkac395
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发表时间：
2022-07-05
影响因子：
14.9
通讯作者：
Schratt, Gerhard
中科院分区：
文献类型：
--
作者：
Soutschek, Michael;Germade, Tomas;Germain, Pierre-Luc;Schratt, Gerhard
MicroRNAs(MiRNAs)是一种小的非编码RNA，是基因表达的主要转录后调节因子之一。一些数据收集和预测工具收集了这些监管机构推定或确认的目标。对于发现和验证，利用这种收集在给定的转录签名或基因集中进行靶标浓缩分析以预测涉及的miRNAs通常是有用的。虽然为此目的提出了几种方法，但缺乏使用各种方法和集合进行这种分析的灵活和用户友好的界面。丰富MiR(https://ethz-ins.org/enrichMiR/))通过使用户能够基于几个目标集合进行一系列浓缩测试来解决这一差距，以根据miRNA可能参与给定转录签名或基因集的控制来对miRNA进行排名。丰富的MiR结果还可以通过交互式和可供发布的绘图进行可视化。为了指导选择合适的分析方法，我们对涉及已知miRNAs扰动的一组实验的各种测试进行了基准测试。最后，我们通过两个用例展示了丰富的MiR功能。丰富的MiR能够在各种目标集合的帮助下从基因签名中识别功能相关的microRNAs，并提供在可供出版的曲线图中可视化结果的可能性。
MicroRNAs (miRNAs) are small non-coding RNAs that are among the main post-transcriptional regulators of gene expression. A number of data collections and prediction tools have gathered putative or confirmed targets of these regulators. It is often useful, for discovery and validation, to harness such collections to perform target enrichment analysis in given transcriptional signatures or gene-sets in order to predict involved miRNAs. While several methods have been proposed to this end, a flexible and user-friendly interface for such analyses using various approaches and collections is lacking. enrichMiR (https://ethz-ins.org/enrichMiR/) addresses this gap by enabling users to perform a series of enrichment tests, based on several target collections, to rank miRNAs according to their likely involvement in the control of a given transcriptional signature or gene-set. enrichMiR results can furthermore be visualised through interactive and publication-ready plots. To guide the choice of the appropriate analysis method, we benchmarked various tests across a panel of experiments involving the perturbation of known miRNAs. Finally, we showcase enrichMiR functionalities in a pair of use cases. enrichMiR enables the identification of functionally relevant microRNAs from gene signatures with the help of various target collections, and offers the possibility to visualize the results in publication-ready plots.
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影响因子：
64.5
作者：
Kleaveland B;Shi CY;Stefano J;Bartel DP
通讯作者：
Bartel DP
DOI：
10.1126/science.aad2509
发表时间：
2015-12-18
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Amin ND;Bai G;Klug JR;Bonanomi D;Pankratz MT;Gifford WD;Hinckley CA;Sternfeld MJ;Driscoll SP;Dominguez B;Lee KF;Jin X;Pfaff SL
通讯作者：
Pfaff SL
影响因子：
7.7
作者：
Colameo D;Rajman M;Soutschek M;Bicker S;von Ziegler L;Bohacek J;Winterer J;Germain PL;Dieterich C;Schratt G
通讯作者：
Schratt G
影响因子：
14.9
作者：
Chang, Le;Zhou, Guangyan;Xia, Jianguo
通讯作者：
Xia, Jianguo
影响因子：
46.9
作者：
Gaidatzis, Dimos;Burger, Lukas;Stadler, Michael B.
通讯作者：
Stadler, Michael B.