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FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data

Exponential growth of high-throughput data and the increasing complexity of omics information have been making processing and interpreting biological data an extremely difficult and daunting task. Here we developed FuncTree (http://bioviz.tokyo/functree), a web-based application for analyzing and vi...

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Detalles Bibliográficos
Autores principales: Uchiyama, Takeru, Irie, Mitsuru, Mori, Hiroshi, Kurokawa, Ken, Yamada, Takuji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431737/
https://www.ncbi.nlm.nih.gov/pubmed/25974630
http://dx.doi.org/10.1371/journal.pone.0126967
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author Uchiyama, Takeru
Irie, Mitsuru
Mori, Hiroshi
Kurokawa, Ken
Yamada, Takuji
author_facet Uchiyama, Takeru
Irie, Mitsuru
Mori, Hiroshi
Kurokawa, Ken
Yamada, Takuji
author_sort Uchiyama, Takeru
collection PubMed
description Exponential growth of high-throughput data and the increasing complexity of omics information have been making processing and interpreting biological data an extremely difficult and daunting task. Here we developed FuncTree (http://bioviz.tokyo/functree), a web-based application for analyzing and visualizing large-scale omics data, including but not limited to genomic, metagenomic, and transcriptomic data. FuncTree allows user to map their omics data onto the “Functional Tree map”, a predefined circular dendrogram, which represents the hierarchical relationship of all known biological functions defined in the KEGG database. This novel visualization method allows user to overview the broad functionality of their data, thus allowing a more accurate and comprehensive understanding of the omics information. FuncTree provides extensive customization and calculation methods to not only allow user to directly map their omics data to identify the functionality of their data, but also to compute statistically enriched functions by comparing it to other predefined omics data. We have validated FuncTree’s analysis and visualization capability by mapping pan-genomic data of three different types of bacterial genera, metagenomic data of the human gut, and transcriptomic data of two different types of human cell expression. All three mapping strongly confirms FuncTree’s capability to analyze and visually represent key functional feature of the omics data. We believe that FuncTree’s capability to conduct various functional calculations and visualizing the result into a holistic overview of biological function, would make it an integral analysis/visualization tool for extensive omics base research.
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spelling pubmed-44317372015-05-27 FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data Uchiyama, Takeru Irie, Mitsuru Mori, Hiroshi Kurokawa, Ken Yamada, Takuji PLoS One Research Article Exponential growth of high-throughput data and the increasing complexity of omics information have been making processing and interpreting biological data an extremely difficult and daunting task. Here we developed FuncTree (http://bioviz.tokyo/functree), a web-based application for analyzing and visualizing large-scale omics data, including but not limited to genomic, metagenomic, and transcriptomic data. FuncTree allows user to map their omics data onto the “Functional Tree map”, a predefined circular dendrogram, which represents the hierarchical relationship of all known biological functions defined in the KEGG database. This novel visualization method allows user to overview the broad functionality of their data, thus allowing a more accurate and comprehensive understanding of the omics information. FuncTree provides extensive customization and calculation methods to not only allow user to directly map their omics data to identify the functionality of their data, but also to compute statistically enriched functions by comparing it to other predefined omics data. We have validated FuncTree’s analysis and visualization capability by mapping pan-genomic data of three different types of bacterial genera, metagenomic data of the human gut, and transcriptomic data of two different types of human cell expression. All three mapping strongly confirms FuncTree’s capability to analyze and visually represent key functional feature of the omics data. We believe that FuncTree’s capability to conduct various functional calculations and visualizing the result into a holistic overview of biological function, would make it an integral analysis/visualization tool for extensive omics base research. Public Library of Science 2015-05-14 /pmc/articles/PMC4431737/ /pubmed/25974630 http://dx.doi.org/10.1371/journal.pone.0126967 Text en © 2015 Uchiyama et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Uchiyama, Takeru
Irie, Mitsuru
Mori, Hiroshi
Kurokawa, Ken
Yamada, Takuji
FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data
title FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data
title_full FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data
title_fullStr FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data
title_full_unstemmed FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data
title_short FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data
title_sort functree: functional analysis and visualization for large-scale omics data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4431737/
https://www.ncbi.nlm.nih.gov/pubmed/25974630
http://dx.doi.org/10.1371/journal.pone.0126967
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