Sangerbox: A comprehensive, interaction‐friendly clinical bioinformatics analysis platform

上传 服务器 Web服务器 计算机科学 生物数据库 生物信息学 功能(生物学) 接口(物质) 数据科学 数据挖掘 万维网 互联网 生物 操作系统 气泡 进化生物学 最大气泡压力法
作者
Weitao Shen,Zhen Song,Xiao Yan Zhong,Mei Huang,Dan‐Ting Shen,Peng Gao,Xiaoqian Qian,Mengmeng Wang,Xingyuan He,Tonglian Wang,Shuang Li,Xuejing Song
出处
期刊:iMeta [Wiley]
卷期号:1 (3) 被引量:446
标识
DOI:10.1002/imt2.36
摘要

Abstract 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 Additionally, some web services are outdated, and inefficient interaction often fails to meet the needs of researchers, such as our previous versions of the platform.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.
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