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Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite

High-throughput gene expression analysis is widely used. However, analysis is not straightforward. Multiple approaches should be applied and methods to combine their results implemented and investigated. We present methodology for the comprehensive analysis of expression data, including co-expressio...

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Autores principales: Jabato, Fernando M., Córdoba-Caballero, José, Rojano, Elena, Romá-Mateo, Carlos, Sanz, Pascual, Pérez, Belén, Gallego, Diana, Seoane, Pedro, Ranea, Juan A. G., Perkins, James R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8302605/
https://www.ncbi.nlm.nih.gov/pubmed/34301987
http://dx.doi.org/10.1038/s41598-021-94343-w
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author Jabato, Fernando M.
Córdoba-Caballero, José
Rojano, Elena
Romá-Mateo, Carlos
Sanz, Pascual
Pérez, Belén
Gallego, Diana
Seoane, Pedro
Ranea, Juan A. G.
Perkins, James R.
author_facet Jabato, Fernando M.
Córdoba-Caballero, José
Rojano, Elena
Romá-Mateo, Carlos
Sanz, Pascual
Pérez, Belén
Gallego, Diana
Seoane, Pedro
Ranea, Juan A. G.
Perkins, James R.
author_sort Jabato, Fernando M.
collection PubMed
description High-throughput gene expression analysis is widely used. However, analysis is not straightforward. Multiple approaches should be applied and methods to combine their results implemented and investigated. We present methodology for the comprehensive analysis of expression data, including co-expression module detection and result integration via data-fusion, threshold based methods, and a Naïve Bayes classifier trained on simulated data. Application to rare-disease model datasets confirms existing knowledge related to immune cell infiltration and suggest novel hypotheses including the role of calcium channels. Application to simulated and spike-in experiments shows that combining multiple methods using consensus and classifiers leads to optimal results. ExpHunter Suite is implemented as an R/Bioconductor package available from https://bioconductor.org/packages/ExpHunterSuite. It can be applied to model and non-model organisms and can be run modularly in R; it can also be run from the command line, allowing scalability with large datasets. Code and reports for the studies are available from https://github.com/fmjabato/ExpHunterSuiteExamples.
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spelling pubmed-83026052021-07-27 Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite Jabato, Fernando M. Córdoba-Caballero, José Rojano, Elena Romá-Mateo, Carlos Sanz, Pascual Pérez, Belén Gallego, Diana Seoane, Pedro Ranea, Juan A. G. Perkins, James R. Sci Rep Article High-throughput gene expression analysis is widely used. However, analysis is not straightforward. Multiple approaches should be applied and methods to combine their results implemented and investigated. We present methodology for the comprehensive analysis of expression data, including co-expression module detection and result integration via data-fusion, threshold based methods, and a Naïve Bayes classifier trained on simulated data. Application to rare-disease model datasets confirms existing knowledge related to immune cell infiltration and suggest novel hypotheses including the role of calcium channels. Application to simulated and spike-in experiments shows that combining multiple methods using consensus and classifiers leads to optimal results. ExpHunter Suite is implemented as an R/Bioconductor package available from https://bioconductor.org/packages/ExpHunterSuite. It can be applied to model and non-model organisms and can be run modularly in R; it can also be run from the command line, allowing scalability with large datasets. Code and reports for the studies are available from https://github.com/fmjabato/ExpHunterSuiteExamples. Nature Publishing Group UK 2021-07-23 /pmc/articles/PMC8302605/ /pubmed/34301987 http://dx.doi.org/10.1038/s41598-021-94343-w 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/) .
spellingShingle Article
Jabato, Fernando M.
Córdoba-Caballero, José
Rojano, Elena
Romá-Mateo, Carlos
Sanz, Pascual
Pérez, Belén
Gallego, Diana
Seoane, Pedro
Ranea, Juan A. G.
Perkins, James R.
Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite
title Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite
title_full Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite
title_fullStr Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite
title_full_unstemmed Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite
title_short Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite
title_sort gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using exphuntersuite
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8302605/
https://www.ncbi.nlm.nih.gov/pubmed/34301987
http://dx.doi.org/10.1038/s41598-021-94343-w
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