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ShinyOmics: collaborative exploration of omics-data

BACKGROUND: Omics-profiling is a collection of increasingly prominent approaches that result in large-scale biological datasets, for instance capturing an organism’s behavior and response in an environment. It can be daunting to manually analyze and interpret such large datasets without some program...

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Autores principales: Surujon, Defne, van Opijnen, Tim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6969480/
https://www.ncbi.nlm.nih.gov/pubmed/31952481
http://dx.doi.org/10.1186/s12859-020-3360-x
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author Surujon, Defne
van Opijnen, Tim
author_facet Surujon, Defne
van Opijnen, Tim
author_sort Surujon, Defne
collection PubMed
description BACKGROUND: Omics-profiling is a collection of increasingly prominent approaches that result in large-scale biological datasets, for instance capturing an organism’s behavior and response in an environment. It can be daunting to manually analyze and interpret such large datasets without some programming experience. Additionally, with increasing amounts of data; management, storage and sharing challenges arise. RESULTS: Here, we present ShinyOmics, a web-based application that allows rapid collaborative exploration of omics-data. By using Tn-Seq, RNA-Seq, microarray and proteomics datasets from two human pathogens, we exemplify several conclusions that can be drawn from a rich dataset. We identify a protease and several chaperone proteins upregulated under aminoglycoside stress, show that antibiotics with the same mechanism of action trigger similar transcriptomic responses, point out the dissimilarity in different omics-profiles, and overlay the transcriptional response on a metabolic network. CONCLUSIONS: ShinyOmics is easy to set up and customize, and can utilize user supplied metadata. It offers several visualization and comparison options that are designed to assist in novel hypothesis generation, as well as data management, online sharing and exploration. Moreover, ShinyOmics can be used as an interactive supplement accompanying research articles or presentations.
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spelling pubmed-69694802020-01-27 ShinyOmics: collaborative exploration of omics-data Surujon, Defne van Opijnen, Tim BMC Bioinformatics Software BACKGROUND: Omics-profiling is a collection of increasingly prominent approaches that result in large-scale biological datasets, for instance capturing an organism’s behavior and response in an environment. It can be daunting to manually analyze and interpret such large datasets without some programming experience. Additionally, with increasing amounts of data; management, storage and sharing challenges arise. RESULTS: Here, we present ShinyOmics, a web-based application that allows rapid collaborative exploration of omics-data. By using Tn-Seq, RNA-Seq, microarray and proteomics datasets from two human pathogens, we exemplify several conclusions that can be drawn from a rich dataset. We identify a protease and several chaperone proteins upregulated under aminoglycoside stress, show that antibiotics with the same mechanism of action trigger similar transcriptomic responses, point out the dissimilarity in different omics-profiles, and overlay the transcriptional response on a metabolic network. CONCLUSIONS: ShinyOmics is easy to set up and customize, and can utilize user supplied metadata. It offers several visualization and comparison options that are designed to assist in novel hypothesis generation, as well as data management, online sharing and exploration. Moreover, ShinyOmics can be used as an interactive supplement accompanying research articles or presentations. BioMed Central 2020-01-17 /pmc/articles/PMC6969480/ /pubmed/31952481 http://dx.doi.org/10.1186/s12859-020-3360-x Text en © The Author(s). 2020 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
Surujon, Defne
van Opijnen, Tim
ShinyOmics: collaborative exploration of omics-data
title ShinyOmics: collaborative exploration of omics-data
title_full ShinyOmics: collaborative exploration of omics-data
title_fullStr ShinyOmics: collaborative exploration of omics-data
title_full_unstemmed ShinyOmics: collaborative exploration of omics-data
title_short ShinyOmics: collaborative exploration of omics-data
title_sort shinyomics: collaborative exploration of omics-data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6969480/
https://www.ncbi.nlm.nih.gov/pubmed/31952481
http://dx.doi.org/10.1186/s12859-020-3360-x
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