Shen Weitao, Song Ziguang, Zhong Xiao, Huang Mei, Shen Danting, Gao Pingping, Qian Xiaoqian, Wang Mengmeng, He Xiubin, Wang Tonglian, Li Shuang, Song Xiang
Bioinformatics R&D Department Hangzhou Mugu Technology Co., Ltd Hangzhou China.
Department of Cardiovascular Medicine Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital Shanghai China.
Imeta. 2022 Jul 8;1(3):e36. doi: 10.1002/imt2.36. eCollection 2022 Sep.
In recent decades, with the continuous development of high-throughput sequencing technology, data volume in medical research has increased, at the same time, almost all clinical researchers have their own independent omics data, which provided a better condition for data mining and a deeper understanding of gene functions. However, for these large amounts of data, many common and cutting-edge effective bioinformatics research methods still cannot be widely used. This has encouraged the establishment of many analytical platforms, a portion of databases or platforms were designed to solve the special analysis needs of users, for instance, MG RAST, IMG/M, Qiita, BIGSdb, and TRAPR were developed for specific omics research, and some databases or servers provide solutions for special problems solutions. Metascape was designed to only provide functional annotations of genes as well as function enrichment analysis; BioNumerics and RidomSeqSphere+ perform multilocus sequence typing; CARD provides only antimicrobial resistance annotations. Additionally, some web services are outdated, and inefficient interaction often fails to meet the needs of researchers, such as our previous versions of the platform. Therefore, the demand to complete massive data processing tasks urgently requires a comprehensive bioinformatics analysis platform. Hence, we have developed a website platform, Sangerbox 3.0 (http://vip.sangerbox.com/), a web-based tool platform. On a user-friendly interface that also supports differential analysis, the platform provides interactive customizable analysis tools, including various kinds of correlation analyses, pathway enrichment analysis, weighted correlation network analysis, and other common tools and functions, users only need to upload their own corresponding data into Sangerbox 3.0, select required parameters, submit, and wait for the results after the task has been completed. We have also established a new interactive plotting system that allows users to adjust the parameters in the image; moreover, optimized plotting performance enables users to adjust large-capacity vector maps on the web site. At the same time, we have integrated GEO, TCGA, ICGC, and other databases and processed data in batches, greatly reducing the difficulty to obtain data and improving the efficiency of bioimformatics study for users. Finally, we also provide users with rich sources of bioinformatics analysis courses, offering a platform for researchers to share and exchange knowledge.
近几十年来,随着高通量测序技术的不断发展,医学研究中的数据量不断增加,与此同时,几乎所有临床研究人员都拥有自己独立的组学数据,这为数据挖掘和更深入了解基因功能提供了更好的条件。然而,对于这些海量数据,许多常见的和前沿的有效生物信息学研究方法仍无法广泛应用。这促使了许多分析平台的建立,一部分数据库或平台旨在解决用户的特殊分析需求,例如,MG RAST、IMG/M、Qiita、BIGSdb和TRAPR是为特定的组学研究而开发的,一些数据库或服务器为特殊问题提供解决方案。Metascape仅设计用于提供基因的功能注释以及功能富集分析;BioNumerics和RidomSeqSphere+进行多位点序列分型;CARD仅提供抗菌药物耐药性注释。此外,一些网络服务过时,低效的交互往往无法满足研究人员的需求,比如我们之前版本的平台。因此,完成海量数据处理任务的需求迫切需要一个综合性的生物信息学分析平台。因此,我们开发了一个网站平台Sangerbox 3.0(http://vip.sangerbox.com/),一个基于网络的工具平台。在一个支持差异分析且用户友好的界面上,该平台提供交互式可定制分析工具,包括各种相关性分析、通路富集分析、加权相关网络分析以及其他常见工具和功能,用户只需将自己相应的数据上传到Sangerbox 3.0,选择所需参数,提交,然后等待任务完成后的结果。我们还建立了一个新的交互式绘图系统,允许用户在图像中调整参数;此外,优化后的绘图性能使用户能够在网站上调整大容量矢量图。同时,我们整合了GEO、TCGA、ICGC等数据库并批量处理数据,极大地降低了用户获取数据的难度,提高了生物信息学研究的效率。最后,我们还为用户提供丰富的生物信息学分析课程资源,为研究人员提供一个知识分享和交流的平台。