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Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization
Abstract Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualizati...
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Published in: | Briefings in bioinformatics 2022-07, Vol.23 (4) |
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creator | Li, Jianfeng Miao, Benben Wang, Shixiang Dong, Wei Xu, Houshi Si, Chenchen Wang, Wei Duan, Songqi Lou, Jiacheng Bao, Zhiwei Zeng, Hailuan Yang, Zengzeng Cheng, Wenyan Zhao, Fei Zeng, Jianming Liu, Xue-Song Wu, Renxie Shen, Yang Chen, Zhu Chen, Saijuan Wang, Mingjie |
description | Abstract
Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service. |
doi_str_mv | 10.1093/bib/bbac261 |
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Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.</description><identifier>ISSN: 1467-5463</identifier><identifier>EISSN: 1477-4054</identifier><identifier>DOI: 10.1093/bib/bbac261</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>Bioinformatics ; Biomedical data ; Clustering ; Data mining ; Data transfer (computers) ; Dimensional analysis ; Health risks ; Medical research ; Parameters ; Risk analysis ; Risk factors ; Scientific visualization ; Statistical analysis ; Survival analysis ; Visualization ; Web services ; Websites</subject><ispartof>Briefings in bioinformatics, 2022-07, Vol.23 (4)</ispartof><rights>The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com 2022</rights><rights>The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-a596d30ab13820305d4b43aa17983d11fd55b46a15a88925bb2a0b5f553cf0ac3</citedby><cites>FETCH-LOGICAL-c362t-a596d30ab13820305d4b43aa17983d11fd55b46a15a88925bb2a0b5f553cf0ac3</cites><orcidid>0000-0001-9855-7357 ; 0000-0002-7307-1331 ; 0000-0003-2349-208X ; 0000-0002-4922-1707 ; 0000-0002-0822-5883</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,1604,27924,27925</link.rule.ids><linktorsrc>$$Uhttps://dx.doi.org/10.1093/bib/bbac261$$EView_record_in_Oxford_University_Press$$FView_record_in_$$GOxford_University_Press</linktorsrc></links><search><creatorcontrib>Li, Jianfeng</creatorcontrib><creatorcontrib>Miao, Benben</creatorcontrib><creatorcontrib>Wang, Shixiang</creatorcontrib><creatorcontrib>Dong, Wei</creatorcontrib><creatorcontrib>Xu, Houshi</creatorcontrib><creatorcontrib>Si, Chenchen</creatorcontrib><creatorcontrib>Wang, Wei</creatorcontrib><creatorcontrib>Duan, Songqi</creatorcontrib><creatorcontrib>Lou, Jiacheng</creatorcontrib><creatorcontrib>Bao, Zhiwei</creatorcontrib><creatorcontrib>Zeng, Hailuan</creatorcontrib><creatorcontrib>Yang, Zengzeng</creatorcontrib><creatorcontrib>Cheng, Wenyan</creatorcontrib><creatorcontrib>Zhao, Fei</creatorcontrib><creatorcontrib>Zeng, Jianming</creatorcontrib><creatorcontrib>Liu, Xue-Song</creatorcontrib><creatorcontrib>Wu, Renxie</creatorcontrib><creatorcontrib>Shen, Yang</creatorcontrib><creatorcontrib>Chen, Zhu</creatorcontrib><creatorcontrib>Chen, Saijuan</creatorcontrib><creatorcontrib>Wang, Mingjie</creatorcontrib><creatorcontrib>Hiplot Consortium</creatorcontrib><title>Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization</title><title>Briefings in bioinformatics</title><description>Abstract
Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.</description><subject>Bioinformatics</subject><subject>Biomedical data</subject><subject>Clustering</subject><subject>Data mining</subject><subject>Data transfer (computers)</subject><subject>Dimensional analysis</subject><subject>Health risks</subject><subject>Medical research</subject><subject>Parameters</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Scientific visualization</subject><subject>Statistical analysis</subject><subject>Survival analysis</subject><subject>Visualization</subject><subject>Web services</subject><subject>Websites</subject><issn>1467-5463</issn><issn>1477-4054</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp90MlKA0EQBuBGFIzRky_QIIggbXqdxZsENwh40fNQvYx2mEyP3TOR-PROTE4ePFVRfPwUP0LnjN4wWoqZ9nqmNRiesQM0YTLPiaRKHm73LCdKZuIYnaS0pJTTvGAT1D35rgn9LQZswqqL7sO1ya8dhtZiB2lD-kCG5PCX0zi5uPbG4TpErENIvW_fcTfoxhvofWhJdGA3WPuwcna8NdhCD3jt0wCN__41p-iohia5s_2coreH-9f5E1m8PD7P7xbEiIz3BFSZWUFBM1FwKqiyUksBwPKyEJax2iqlZQZMQVGUXGnNgWpVKyVMTcGIKbra5XYxfA4u9dXKJ-OaBloXhlTxrFBUCMHlSC_-0GUYYjt-N6qyVCUXlI7qeqdMDClFV1dd9CuIm4rRatt-NbZf7dsf9eVOh6H7F_4As16GnQ</recordid><startdate>20220718</startdate><enddate>20220718</enddate><creator>Li, Jianfeng</creator><creator>Miao, Benben</creator><creator>Wang, Shixiang</creator><creator>Dong, Wei</creator><creator>Xu, Houshi</creator><creator>Si, Chenchen</creator><creator>Wang, Wei</creator><creator>Duan, Songqi</creator><creator>Lou, Jiacheng</creator><creator>Bao, Zhiwei</creator><creator>Zeng, Hailuan</creator><creator>Yang, Zengzeng</creator><creator>Cheng, Wenyan</creator><creator>Zhao, Fei</creator><creator>Zeng, Jianming</creator><creator>Liu, Xue-Song</creator><creator>Wu, Renxie</creator><creator>Shen, Yang</creator><creator>Chen, Zhu</creator><creator>Chen, Saijuan</creator><creator>Wang, Mingjie</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7SC</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>K9.</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9855-7357</orcidid><orcidid>https://orcid.org/0000-0002-7307-1331</orcidid><orcidid>https://orcid.org/0000-0003-2349-208X</orcidid><orcidid>https://orcid.org/0000-0002-4922-1707</orcidid><orcidid>https://orcid.org/0000-0002-0822-5883</orcidid></search><sort><creationdate>20220718</creationdate><title>Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization</title><author>Li, Jianfeng ; Miao, Benben ; Wang, Shixiang ; Dong, Wei ; Xu, Houshi ; Si, Chenchen ; Wang, Wei ; Duan, Songqi ; Lou, Jiacheng ; Bao, Zhiwei ; Zeng, Hailuan ; Yang, Zengzeng ; Cheng, Wenyan ; Zhao, Fei ; Zeng, Jianming ; Liu, Xue-Song ; Wu, Renxie ; Shen, Yang ; Chen, Zhu ; Chen, Saijuan ; Wang, Mingjie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-a596d30ab13820305d4b43aa17983d11fd55b46a15a88925bb2a0b5f553cf0ac3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Bioinformatics</topic><topic>Biomedical data</topic><topic>Clustering</topic><topic>Data mining</topic><topic>Data transfer (computers)</topic><topic>Dimensional analysis</topic><topic>Health risks</topic><topic>Medical research</topic><topic>Parameters</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Scientific visualization</topic><topic>Statistical analysis</topic><topic>Survival analysis</topic><topic>Visualization</topic><topic>Web services</topic><topic>Websites</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Jianfeng</creatorcontrib><creatorcontrib>Miao, Benben</creatorcontrib><creatorcontrib>Wang, Shixiang</creatorcontrib><creatorcontrib>Dong, Wei</creatorcontrib><creatorcontrib>Xu, Houshi</creatorcontrib><creatorcontrib>Si, Chenchen</creatorcontrib><creatorcontrib>Wang, Wei</creatorcontrib><creatorcontrib>Duan, Songqi</creatorcontrib><creatorcontrib>Lou, Jiacheng</creatorcontrib><creatorcontrib>Bao, Zhiwei</creatorcontrib><creatorcontrib>Zeng, Hailuan</creatorcontrib><creatorcontrib>Yang, Zengzeng</creatorcontrib><creatorcontrib>Cheng, Wenyan</creatorcontrib><creatorcontrib>Zhao, Fei</creatorcontrib><creatorcontrib>Zeng, Jianming</creatorcontrib><creatorcontrib>Liu, Xue-Song</creatorcontrib><creatorcontrib>Wu, Renxie</creatorcontrib><creatorcontrib>Shen, Yang</creatorcontrib><creatorcontrib>Chen, Zhu</creatorcontrib><creatorcontrib>Chen, Saijuan</creatorcontrib><creatorcontrib>Wang, Mingjie</creatorcontrib><creatorcontrib>Hiplot Consortium</creatorcontrib><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Briefings in bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Li, Jianfeng</au><au>Miao, Benben</au><au>Wang, Shixiang</au><au>Dong, Wei</au><au>Xu, Houshi</au><au>Si, Chenchen</au><au>Wang, Wei</au><au>Duan, Songqi</au><au>Lou, Jiacheng</au><au>Bao, Zhiwei</au><au>Zeng, Hailuan</au><au>Yang, Zengzeng</au><au>Cheng, Wenyan</au><au>Zhao, Fei</au><au>Zeng, Jianming</au><au>Liu, Xue-Song</au><au>Wu, Renxie</au><au>Shen, Yang</au><au>Chen, Zhu</au><au>Chen, Saijuan</au><au>Wang, Mingjie</au><aucorp>Hiplot Consortium</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization</atitle><jtitle>Briefings in bioinformatics</jtitle><date>2022-07-18</date><risdate>2022</risdate><volume>23</volume><issue>4</issue><issn>1467-5463</issn><eissn>1477-4054</eissn><abstract>Abstract
Complex biomedical data generated during clinical, omics and mechanism-based experiments have increasingly been exploited through cloud- and visualization-based data mining techniques. However, the scientific community still lacks an easy-to-use web service for the comprehensive visualization of biomedical data, particularly high-quality and publication-ready graphics that allow easy scaling and updatability according to user demands. Therefore, we propose a community-driven modern web service, Hiplot (https://hiplot.org), with concise and top-quality data visualization applications for the life sciences and biomedical fields. This web service permits users to conveniently and interactively complete a few specialized visualization tasks that previously could only be conducted by senior bioinformatics or biostatistics researchers. It covers most of the daily demands of biomedical researchers with its equipped 240+ biomedical data visualization functions, involving basic statistics, multi-omics, regression, clustering, dimensional reduction, meta-analysis, survival analysis, risk modelling, etc. Moreover, to improve the efficiency in use and development of plugins, we introduced some core advantages on the client-/server-side of the website, such as spreadsheet-based data importing, cross-platform command-line controller (Hctl), multi-user plumber workers, JavaScript Object Notation-based plugin system, easy data/parameters, results and errors reproduction and real-time updates mode. Meanwhile, using demo/real data sets and benchmark tests, we explored statistical parameters, cancer genomic landscapes, disease risk factors and the performance of website based on selected native plugins. The statistics of visits and user numbers could further reflect the potential impact of this web service on relevant fields. Thus, researchers devoted to life and data sciences would benefit from this emerging and free web service.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><doi>10.1093/bib/bbac261</doi><orcidid>https://orcid.org/0000-0001-9855-7357</orcidid><orcidid>https://orcid.org/0000-0002-7307-1331</orcidid><orcidid>https://orcid.org/0000-0003-2349-208X</orcidid><orcidid>https://orcid.org/0000-0002-4922-1707</orcidid><orcidid>https://orcid.org/0000-0002-0822-5883</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Bioinformatics Biomedical data Clustering Data mining Data transfer (computers) Dimensional analysis Health risks Medical research Parameters Risk analysis Risk factors Scientific visualization Statistical analysis Survival analysis Visualization Web services Websites |
title | Hiplot: a comprehensive and easy-to-use web service for boosting publication-ready biomedical data visualization |
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