It has become increasingly challenging for researchers to analyze the exponentially expanding multi-omic data. In this project, we have developed a multi-functional software named evolutionary Genotype-Phenotype Systems (eGPS) that enables users to perform comprehensive multi-omic and evolutionary analyses. The eGPS combines the power of cloud computing and the advantage of desktop application, has a user-friendly graphic interface, and is highly interactive. Moreover, third-party plugins are supported and the developers can take the credits for contributing the plugins. This makes it easier for the community to implement new modules and also encourages their sharing. The eGPS not only develops the new functions/tools/methods but also bridges the gap between multi-omic and evolutionary analyses.
How to cite
1. Dalang Yu, Lili Dong, Fangqi Yan, Hailong Mu, Bixia Tang, et al. (2019) eGPS 1.0: comprehensive software for multi-omic and evolutionary analyses. National Science Review, 6(5):867-869, https://doi.org/10.1093/nsr/nwz079
2. Dalang Yu, Xiao Yang, Bixia Tang, Yi-Hsuan Pan, Jianing Yang, Guangya Duan, Junwei Zhu, Zi-Qian Hao, Hailong Mu, Long Dai, Wangjie Hu, Mochen Zhang, Ying Cui, Tong Jin, Cui-Ping Li, Lina Ma, Language translation team, Xiao Su, Guoqing Zhang, Wenming Zhao, Haipeng Li, Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2, Briefings in Bioinformatics, 2022; bbab583 https://doi.org/10.1093/bib/bbab583
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