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ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration

Tremendous amount of whole-genome sequencing data have been provided by large consortium projects such as TCGA (The Cancer Genome Atlas), COSMIC and so on, which creates incredible opportunities for functional gene research and cancer associated mechanism uncovering. While the existing web servers a...

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Autores principales: Bi, Jia-Hao, Tong, Yi-Fan, Qiu, Zhe-Wei, Yang, Xing-Feng, Minna, John, Gazdar, Adi F., Song, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6595587/
https://www.ncbi.nlm.nih.gov/pubmed/31391866
http://dx.doi.org/10.1186/s13040-019-0202-3
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author Bi, Jia-Hao
Tong, Yi-Fan
Qiu, Zhe-Wei
Yang, Xing-Feng
Minna, John
Gazdar, Adi F.
Song, Kai
author_facet Bi, Jia-Hao
Tong, Yi-Fan
Qiu, Zhe-Wei
Yang, Xing-Feng
Minna, John
Gazdar, Adi F.
Song, Kai
author_sort Bi, Jia-Hao
collection PubMed
description Tremendous amount of whole-genome sequencing data have been provided by large consortium projects such as TCGA (The Cancer Genome Atlas), COSMIC and so on, which creates incredible opportunities for functional gene research and cancer associated mechanism uncovering. While the existing web servers are valuable and widely used, many whole genome analysis functions urgently needed by experimental biologists are still not adequately addressed. A cloud-based platform, named CG (ClickGene), therefore, was developed for DIY analyzing of user’s private in-house data or public genome data without any requirement of software installation or system configuration. CG platform provides key interactive and customized functions including Bee-swarm plot, linear regression analyses, Mountain plot, Directional Manhattan plot, Deflection plot and Volcano plot. Using these tools, global profiling or individual gene distributions for expression and copy number variation (CNV) analyses can be generated by only mouse button clicking. The easy accessibility of such comprehensive pan-cancer genome analysis greatly facilitates data mining in wide research areas, such as therapeutic discovery process. Therefore, it fills in the gaps between big cancer genomics data and the delivery of integrated knowledge to end-users, thus helping unleash the value of the current data resources. More importantly, unlike other R-based web platforms, Dubbo, a cloud distributed service governance framework for ‘big data’ stream global transferring, was used to develop CG platform. After being developed, CG is run on an independent cloud-server, which ensures its steady global accessibility. More than 2 years running history of CG proved that advanced plots for hundreds of whole-genome data can be created through it within seconds by end-users anytime and anywhere. CG is available at http://www.clickgenome.org/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13040-019-0202-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-65955872019-08-07 ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration Bi, Jia-Hao Tong, Yi-Fan Qiu, Zhe-Wei Yang, Xing-Feng Minna, John Gazdar, Adi F. Song, Kai BioData Min Software Article Tremendous amount of whole-genome sequencing data have been provided by large consortium projects such as TCGA (The Cancer Genome Atlas), COSMIC and so on, which creates incredible opportunities for functional gene research and cancer associated mechanism uncovering. While the existing web servers are valuable and widely used, many whole genome analysis functions urgently needed by experimental biologists are still not adequately addressed. A cloud-based platform, named CG (ClickGene), therefore, was developed for DIY analyzing of user’s private in-house data or public genome data without any requirement of software installation or system configuration. CG platform provides key interactive and customized functions including Bee-swarm plot, linear regression analyses, Mountain plot, Directional Manhattan plot, Deflection plot and Volcano plot. Using these tools, global profiling or individual gene distributions for expression and copy number variation (CNV) analyses can be generated by only mouse button clicking. The easy accessibility of such comprehensive pan-cancer genome analysis greatly facilitates data mining in wide research areas, such as therapeutic discovery process. Therefore, it fills in the gaps between big cancer genomics data and the delivery of integrated knowledge to end-users, thus helping unleash the value of the current data resources. More importantly, unlike other R-based web platforms, Dubbo, a cloud distributed service governance framework for ‘big data’ stream global transferring, was used to develop CG platform. After being developed, CG is run on an independent cloud-server, which ensures its steady global accessibility. More than 2 years running history of CG proved that advanced plots for hundreds of whole-genome data can be created through it within seconds by end-users anytime and anywhere. CG is available at http://www.clickgenome.org/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13040-019-0202-3) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-26 /pmc/articles/PMC6595587/ /pubmed/31391866 http://dx.doi.org/10.1186/s13040-019-0202-3 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software Article
Bi, Jia-Hao
Tong, Yi-Fan
Qiu, Zhe-Wei
Yang, Xing-Feng
Minna, John
Gazdar, Adi F.
Song, Kai
ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration
title ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration
title_full ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration
title_fullStr ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration
title_full_unstemmed ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration
title_short ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration
title_sort clickgene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration
topic Software Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6595587/
https://www.ncbi.nlm.nih.gov/pubmed/31391866
http://dx.doi.org/10.1186/s13040-019-0202-3
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