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MONGKIE: an integrated tool for network analysis and visualization for multi-omics data

BACKGROUND: Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be...

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Autores principales: Jang, Yeongjun, Yu, Namhee, Seo, Jihae, Kim, Sun, Lee, Sanghyuk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797132/
https://www.ncbi.nlm.nih.gov/pubmed/26987515
http://dx.doi.org/10.1186/s13062-016-0112-y
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author Jang, Yeongjun
Yu, Namhee
Seo, Jihae
Kim, Sun
Lee, Sanghyuk
author_facet Jang, Yeongjun
Yu, Namhee
Seo, Jihae
Kim, Sun
Lee, Sanghyuk
author_sort Jang, Yeongjun
collection PubMed
description BACKGROUND: Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. RESULTS: Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. CONCLUSION: We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. REVIEWERS: This article was reviewed by Prof. Limsoon Wong, Prof. Soojin Yi, and Prof. David Kreil. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13062-016-0112-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-47971322016-03-18 MONGKIE: an integrated tool for network analysis and visualization for multi-omics data Jang, Yeongjun Yu, Namhee Seo, Jihae Kim, Sun Lee, Sanghyuk Biol Direct Application Note BACKGROUND: Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. RESULTS: Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. CONCLUSION: We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. REVIEWERS: This article was reviewed by Prof. Limsoon Wong, Prof. Soojin Yi, and Prof. David Kreil. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13062-016-0112-y) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-18 /pmc/articles/PMC4797132/ /pubmed/26987515 http://dx.doi.org/10.1186/s13062-016-0112-y Text en © Jang et al. 2016 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 Application Note
Jang, Yeongjun
Yu, Namhee
Seo, Jihae
Kim, Sun
Lee, Sanghyuk
MONGKIE: an integrated tool for network analysis and visualization for multi-omics data
title MONGKIE: an integrated tool for network analysis and visualization for multi-omics data
title_full MONGKIE: an integrated tool for network analysis and visualization for multi-omics data
title_fullStr MONGKIE: an integrated tool for network analysis and visualization for multi-omics data
title_full_unstemmed MONGKIE: an integrated tool for network analysis and visualization for multi-omics data
title_short MONGKIE: an integrated tool for network analysis and visualization for multi-omics data
title_sort mongkie: an integrated tool for network analysis and visualization for multi-omics data
topic Application Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797132/
https://www.ncbi.nlm.nih.gov/pubmed/26987515
http://dx.doi.org/10.1186/s13062-016-0112-y
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