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iDINGO—integrative differential network analysis in genomics with Shiny application
MOTIVATION: Differential network analysis is an important way to understand network rewiring involved in disease progression and development. Building differential networks from multiple ‘omics data provides insight into the holistic differences of the interactive system under different patient-spec...
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/PMC6030922/ https://www.ncbi.nlm.nih.gov/pubmed/29194470 http://dx.doi.org/10.1093/bioinformatics/btx750 |
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author | Class, Caleb A Ha, Min Jin Baladandayuthapani, Veerabhadran Do, Kim-Anh |
author_facet | Class, Caleb A Ha, Min Jin Baladandayuthapani, Veerabhadran Do, Kim-Anh |
author_sort | Class, Caleb A |
collection | PubMed |
description | MOTIVATION: Differential network analysis is an important way to understand network rewiring involved in disease progression and development. Building differential networks from multiple ‘omics data provides insight into the holistic differences of the interactive system under different patient-specific groups. DINGO was developed to infer group-specific dependencies and build differential networks. However, DINGO and other existing tools are limited to analyze data arising from a single platform, and modeling each of the multiple ‘omics data independently does not account for the hierarchical structure of the data. RESULTS: We developed the iDINGO R package to estimate group-specific dependencies and make inferences on the integrative differential networks, considering the biological hierarchy among the platforms. A Shiny application has also been developed to facilitate easier analysis and visualization of results, including integrative differential networks and hub gene identification across platforms. AVAILABILITY AND IMPLEMENTATION: R package is available on CRAN (https://cran.r-project.org/web/packages/iDINGO) and Shiny application at https://github.com/MinJinHa/iDINGO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6030922 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60309222018-07-10 iDINGO—integrative differential network analysis in genomics with Shiny application Class, Caleb A Ha, Min Jin Baladandayuthapani, Veerabhadran Do, Kim-Anh Bioinformatics Applications Notes MOTIVATION: Differential network analysis is an important way to understand network rewiring involved in disease progression and development. Building differential networks from multiple ‘omics data provides insight into the holistic differences of the interactive system under different patient-specific groups. DINGO was developed to infer group-specific dependencies and build differential networks. However, DINGO and other existing tools are limited to analyze data arising from a single platform, and modeling each of the multiple ‘omics data independently does not account for the hierarchical structure of the data. RESULTS: We developed the iDINGO R package to estimate group-specific dependencies and make inferences on the integrative differential networks, considering the biological hierarchy among the platforms. A Shiny application has also been developed to facilitate easier analysis and visualization of results, including integrative differential networks and hub gene identification across platforms. AVAILABILITY AND IMPLEMENTATION: R package is available on CRAN (https://cran.r-project.org/web/packages/iDINGO) and Shiny application at https://github.com/MinJinHa/iDINGO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-04-01 2017-11-29 /pmc/articles/PMC6030922/ /pubmed/29194470 http://dx.doi.org/10.1093/bioinformatics/btx750 Text en © The Author 2017. 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 | Applications Notes Class, Caleb A Ha, Min Jin Baladandayuthapani, Veerabhadran Do, Kim-Anh iDINGO—integrative differential network analysis in genomics with Shiny application |
title | iDINGO—integrative differential network analysis in genomics with Shiny application |
title_full | iDINGO—integrative differential network analysis in genomics with Shiny application |
title_fullStr | iDINGO—integrative differential network analysis in genomics with Shiny application |
title_full_unstemmed | iDINGO—integrative differential network analysis in genomics with Shiny application |
title_short | iDINGO—integrative differential network analysis in genomics with Shiny application |
title_sort | idingo—integrative differential network analysis in genomics with shiny application |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030922/ https://www.ncbi.nlm.nih.gov/pubmed/29194470 http://dx.doi.org/10.1093/bioinformatics/btx750 |
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