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Maser: one-stop platform for NGS big data from analysis to visualization
A major challenge in analyzing the data from high-throughput next-generation sequencing (NGS) is how to handle the huge amounts of data and variety of NGS tools and visualize the resultant outputs. To address these issues, we developed a cloud-based data analysis platform, Maser (Management and Anal...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905357/ https://www.ncbi.nlm.nih.gov/pubmed/29688385 http://dx.doi.org/10.1093/database/bay027 |
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author | Kinjo, Sonoko Monma, Norikazu Misu, Sadahiko Kitamura, Norikazu Imoto, Junichi Yoshitake, Kazutoshi Gojobori, Takashi Ikeo, Kazuho |
author_facet | Kinjo, Sonoko Monma, Norikazu Misu, Sadahiko Kitamura, Norikazu Imoto, Junichi Yoshitake, Kazutoshi Gojobori, Takashi Ikeo, Kazuho |
author_sort | Kinjo, Sonoko |
collection | PubMed |
description | A major challenge in analyzing the data from high-throughput next-generation sequencing (NGS) is how to handle the huge amounts of data and variety of NGS tools and visualize the resultant outputs. To address these issues, we developed a cloud-based data analysis platform, Maser (Management and Analysis System for Enormous Reads), and an original genome browser, Genome Explorer (GE). Maser enables users to manage up to 2 terabytes of data to conduct analyses with easy graphical user interface operations and offers analysis pipelines in which several individual tools are combined as a single pipeline for very common and standard analyses. GE automatically visualizes genome assembly and mapping results output from Maser pipelines, without requiring additional data upload. With this function, the Maser pipelines can graphically display the results output from all the embedded tools and mapping results in a web browser. Therefore Maser realized a more user-friendly analysis platform especially for beginners by improving graphical display and providing the selected standard pipelines that work with built-in genome browser. In addition, all the analyses executed on Maser are recorded in the analysis history, helping users to trace and repeat the analyses. The entire process of analysis and its histories can be shared with collaborators or opened to the public. In conclusion, our system is useful for managing, analyzing, and visualizing NGS data and achieves traceability, reproducibility, and transparency of NGS analysis. Database URL: http://cell-innovation.nig.ac.jp/maser/ |
format | Online Article Text |
id | pubmed-5905357 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-59053572018-04-23 Maser: one-stop platform for NGS big data from analysis to visualization Kinjo, Sonoko Monma, Norikazu Misu, Sadahiko Kitamura, Norikazu Imoto, Junichi Yoshitake, Kazutoshi Gojobori, Takashi Ikeo, Kazuho Database (Oxford) Database Tool A major challenge in analyzing the data from high-throughput next-generation sequencing (NGS) is how to handle the huge amounts of data and variety of NGS tools and visualize the resultant outputs. To address these issues, we developed a cloud-based data analysis platform, Maser (Management and Analysis System for Enormous Reads), and an original genome browser, Genome Explorer (GE). Maser enables users to manage up to 2 terabytes of data to conduct analyses with easy graphical user interface operations and offers analysis pipelines in which several individual tools are combined as a single pipeline for very common and standard analyses. GE automatically visualizes genome assembly and mapping results output from Maser pipelines, without requiring additional data upload. With this function, the Maser pipelines can graphically display the results output from all the embedded tools and mapping results in a web browser. Therefore Maser realized a more user-friendly analysis platform especially for beginners by improving graphical display and providing the selected standard pipelines that work with built-in genome browser. In addition, all the analyses executed on Maser are recorded in the analysis history, helping users to trace and repeat the analyses. The entire process of analysis and its histories can be shared with collaborators or opened to the public. In conclusion, our system is useful for managing, analyzing, and visualizing NGS data and achieves traceability, reproducibility, and transparency of NGS analysis. Database URL: http://cell-innovation.nig.ac.jp/maser/ Oxford University Press 2018-04-13 /pmc/articles/PMC5905357/ /pubmed/29688385 http://dx.doi.org/10.1093/database/bay027 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Tool Kinjo, Sonoko Monma, Norikazu Misu, Sadahiko Kitamura, Norikazu Imoto, Junichi Yoshitake, Kazutoshi Gojobori, Takashi Ikeo, Kazuho Maser: one-stop platform for NGS big data from analysis to visualization |
title | Maser: one-stop platform for NGS big data from analysis to visualization |
title_full | Maser: one-stop platform for NGS big data from analysis to visualization |
title_fullStr | Maser: one-stop platform for NGS big data from analysis to visualization |
title_full_unstemmed | Maser: one-stop platform for NGS big data from analysis to visualization |
title_short | Maser: one-stop platform for NGS big data from analysis to visualization |
title_sort | maser: one-stop platform for ngs big data from analysis to visualization |
topic | Database Tool |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5905357/ https://www.ncbi.nlm.nih.gov/pubmed/29688385 http://dx.doi.org/10.1093/database/bay027 |
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