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Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways
BACKGROUND: Interpreting large-scale studies from microarrays or next-generation sequencing for further experimental testing remains one of the major challenges in quantitative biology. Combining expression with physical or genetic interaction data has already been successfully applied to enhance kn...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4606501/ https://www.ncbi.nlm.nih.gov/pubmed/26467653 http://dx.doi.org/10.1186/s12864-015-2017-z |
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author | Garmhausen, Marius Hofmann, Falko Senderov, Viktor Thomas, Maria Kandel, Benjamin A. Habermann, Bianca Hermine |
author_facet | Garmhausen, Marius Hofmann, Falko Senderov, Viktor Thomas, Maria Kandel, Benjamin A. Habermann, Bianca Hermine |
author_sort | Garmhausen, Marius |
collection | PubMed |
description | BACKGROUND: Interpreting large-scale studies from microarrays or next-generation sequencing for further experimental testing remains one of the major challenges in quantitative biology. Combining expression with physical or genetic interaction data has already been successfully applied to enhance knowledge from all types of high-throughput studies. Yet, toolboxes for navigating and understanding even small gene or protein networks are poorly developed. RESULTS: We introduce two Cytoscape plug-ins, which support the generation and interpretation of experiment-based interaction networks. The virtual pathway explorer viPEr creates so-called focus networks by joining a list of experimentally determined genes with the interactome of a specific organism. viPEr calculates all paths between two or more user-selected nodes, or explores the neighborhood of a single selected node. Numerical values from expression studies assigned to the nodes serve to score identified paths. The pathway enrichment analysis tool PEANuT annotates networks with pathway information from various sources and calculates enriched pathways between a focus and a background network. Using time series expression data of atorvastatin treated primary hepatocytes from six patients, we demonstrate the handling and applicability of viPEr and PEANuT. Based on our investigations using viPEr and PEANuT, we suggest a role of the FoxA1/A2/A3 transcriptional network in the cellular response to atorvastatin treatment. Moreover, we find an enrichment of metabolic and cancer pathways in the Fox transcriptional network and demonstrate a patient-specific reaction to the drug. CONCLUSIONS: The Cytoscape plug-in viPEr integrates –omics data with interactome data. It supports the interpretation and navigation of large-scale datasets by creating focus networks, facilitating mechanistic predictions from –omics studies. PEANuT provides an up-front method to identify underlying biological principles by calculating enriched pathways in focus networks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2017-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4606501 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46065012015-10-16 Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways Garmhausen, Marius Hofmann, Falko Senderov, Viktor Thomas, Maria Kandel, Benjamin A. Habermann, Bianca Hermine BMC Genomics Software BACKGROUND: Interpreting large-scale studies from microarrays or next-generation sequencing for further experimental testing remains one of the major challenges in quantitative biology. Combining expression with physical or genetic interaction data has already been successfully applied to enhance knowledge from all types of high-throughput studies. Yet, toolboxes for navigating and understanding even small gene or protein networks are poorly developed. RESULTS: We introduce two Cytoscape plug-ins, which support the generation and interpretation of experiment-based interaction networks. The virtual pathway explorer viPEr creates so-called focus networks by joining a list of experimentally determined genes with the interactome of a specific organism. viPEr calculates all paths between two or more user-selected nodes, or explores the neighborhood of a single selected node. Numerical values from expression studies assigned to the nodes serve to score identified paths. The pathway enrichment analysis tool PEANuT annotates networks with pathway information from various sources and calculates enriched pathways between a focus and a background network. Using time series expression data of atorvastatin treated primary hepatocytes from six patients, we demonstrate the handling and applicability of viPEr and PEANuT. Based on our investigations using viPEr and PEANuT, we suggest a role of the FoxA1/A2/A3 transcriptional network in the cellular response to atorvastatin treatment. Moreover, we find an enrichment of metabolic and cancer pathways in the Fox transcriptional network and demonstrate a patient-specific reaction to the drug. CONCLUSIONS: The Cytoscape plug-in viPEr integrates –omics data with interactome data. It supports the interpretation and navigation of large-scale datasets by creating focus networks, facilitating mechanistic predictions from –omics studies. PEANuT provides an up-front method to identify underlying biological principles by calculating enriched pathways in focus networks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2017-z) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-14 /pmc/articles/PMC4606501/ /pubmed/26467653 http://dx.doi.org/10.1186/s12864-015-2017-z Text en © Garmhausen et al. 2015 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 Garmhausen, Marius Hofmann, Falko Senderov, Viktor Thomas, Maria Kandel, Benjamin A. Habermann, Bianca Hermine Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways |
title | Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways |
title_full | Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways |
title_fullStr | Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways |
title_full_unstemmed | Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways |
title_short | Virtual pathway explorer (viPEr) and pathway enrichment analysis tool (PEANuT): creating and analyzing focus networks to identify cross-talk between molecules and pathways |
title_sort | virtual pathway explorer (viper) and pathway enrichment analysis tool (peanut): creating and analyzing focus networks to identify cross-talk between molecules and pathways |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4606501/ https://www.ncbi.nlm.nih.gov/pubmed/26467653 http://dx.doi.org/10.1186/s12864-015-2017-z |
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