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GraphOmics: an interactive platform to explore and integrate multi-omics data
BACKGROUND: An increasing number of studies now produce multiple omics measurements that require using sophisticated computational methods for analysis. While each omics data can be examined separately, jointly integrating multiple omics data allows for deeper understanding and insights to be gained...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684259/ https://www.ncbi.nlm.nih.gov/pubmed/34922446 http://dx.doi.org/10.1186/s12859-021-04500-1 |
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author | Wandy, Joe Daly, Rónán |
author_facet | Wandy, Joe Daly, Rónán |
author_sort | Wandy, Joe |
collection | PubMed |
description | BACKGROUND: An increasing number of studies now produce multiple omics measurements that require using sophisticated computational methods for analysis. While each omics data can be examined separately, jointly integrating multiple omics data allows for deeper understanding and insights to be gained from the study. In particular, data integration can be performed horizontally, where biological entities from multiple omics measurements are mapped to common reactions and pathways. However, data integration remains a challenge due to the complexity of the data and the difficulty in interpreting analysis results. RESULTS: Here we present GraphOmics, a user-friendly platform to explore and integrate multiple omics datasets and support hypothesis generation. Users can upload transcriptomics, proteomics and metabolomics data to GraphOmics. Relevant entities are connected based on their biochemical relationships, and mapped to reactions and pathways from Reactome. From the Data Browser in GraphOmics, mapped entities and pathways can be ranked, sorted and filtered according to their statistical significance (p values) and fold changes. Context-sensitive panels provide information on the currently selected entities, while interactive heatmaps and clustering functionalities are also available. As a case study, we demonstrated how GraphOmics was used to interactively explore multi-omics data and support hypothesis generation using two complex datasets from existing Zebrafish regeneration and Covid-19 human studies. CONCLUSIONS: GraphOmics is fully open-sourced and freely accessible from https://graphomics.glasgowcompbio.org/. It can be used to integrate multiple omics data horizontally by mapping entities across omics to reactions and pathways. Our demonstration showed that by using interactive explorations from GraphOmics, interesting insights and biological hypotheses could be rapidly revealed. |
format | Online Article Text |
id | pubmed-8684259 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86842592021-12-20 GraphOmics: an interactive platform to explore and integrate multi-omics data Wandy, Joe Daly, Rónán BMC Bioinformatics Software BACKGROUND: An increasing number of studies now produce multiple omics measurements that require using sophisticated computational methods for analysis. While each omics data can be examined separately, jointly integrating multiple omics data allows for deeper understanding and insights to be gained from the study. In particular, data integration can be performed horizontally, where biological entities from multiple omics measurements are mapped to common reactions and pathways. However, data integration remains a challenge due to the complexity of the data and the difficulty in interpreting analysis results. RESULTS: Here we present GraphOmics, a user-friendly platform to explore and integrate multiple omics datasets and support hypothesis generation. Users can upload transcriptomics, proteomics and metabolomics data to GraphOmics. Relevant entities are connected based on their biochemical relationships, and mapped to reactions and pathways from Reactome. From the Data Browser in GraphOmics, mapped entities and pathways can be ranked, sorted and filtered according to their statistical significance (p values) and fold changes. Context-sensitive panels provide information on the currently selected entities, while interactive heatmaps and clustering functionalities are also available. As a case study, we demonstrated how GraphOmics was used to interactively explore multi-omics data and support hypothesis generation using two complex datasets from existing Zebrafish regeneration and Covid-19 human studies. CONCLUSIONS: GraphOmics is fully open-sourced and freely accessible from https://graphomics.glasgowcompbio.org/. It can be used to integrate multiple omics data horizontally by mapping entities across omics to reactions and pathways. Our demonstration showed that by using interactive explorations from GraphOmics, interesting insights and biological hypotheses could be rapidly revealed. BioMed Central 2021-12-18 /pmc/articles/PMC8684259/ /pubmed/34922446 http://dx.doi.org/10.1186/s12859-021-04500-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Wandy, Joe Daly, Rónán GraphOmics: an interactive platform to explore and integrate multi-omics data |
title | GraphOmics: an interactive platform to explore and integrate multi-omics data |
title_full | GraphOmics: an interactive platform to explore and integrate multi-omics data |
title_fullStr | GraphOmics: an interactive platform to explore and integrate multi-omics data |
title_full_unstemmed | GraphOmics: an interactive platform to explore and integrate multi-omics data |
title_short | GraphOmics: an interactive platform to explore and integrate multi-omics data |
title_sort | graphomics: an interactive platform to explore and integrate multi-omics data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8684259/ https://www.ncbi.nlm.nih.gov/pubmed/34922446 http://dx.doi.org/10.1186/s12859-021-04500-1 |
work_keys_str_mv | AT wandyjoe graphomicsaninteractiveplatformtoexploreandintegratemultiomicsdata AT dalyronan graphomicsaninteractiveplatformtoexploreandintegratemultiomicsdata |