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

Abstract 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-...

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Autores principales:	Fernando M. Jabato, José Córdoba-Caballero, Elena Rojano, Carlos Romá-Mateo, Pascual Sanz, Belén Pérez, Diana Gallego, Pedro Seoane, Juan A. G. Ranea, James R. Perkins
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/35510445a6824f5eb37caeaab2b029f1
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spelling	oai:doaj.org-article:35510445a6824f5eb37caeaab2b029f12021-12-02T16:26:29ZGene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite10.1038/s41598-021-94343-w2045-2322https://doaj.org/article/35510445a6824f5eb37caeaab2b029f12021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94343-whttps://doaj.org/toc/2045-2322Abstract 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 .Fernando M. JabatoJosé Córdoba-CaballeroElena RojanoCarlos Romá-MateoPascual SanzBelén PérezDiana GallegoPedro SeoaneJuan A. G. RaneaJames R. PerkinsNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Fernando M. Jabato José Córdoba-Caballero Elena Rojano Carlos Romá-Mateo Pascual Sanz Belén Pérez Diana Gallego Pedro Seoane Juan A. G. Ranea James R. Perkins Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite
description	Abstract 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 .
format	article
author	Fernando M. Jabato José Córdoba-Caballero Elena Rojano Carlos Romá-Mateo Pascual Sanz Belén Pérez Diana Gallego Pedro Seoane Juan A. G. Ranea James R. Perkins
author_facet	Fernando M. Jabato José Córdoba-Caballero Elena Rojano Carlos Romá-Mateo Pascual Sanz Belén Pérez Diana Gallego Pedro Seoane Juan A. G. Ranea James R. Perkins
author_sort	Fernando M. Jabato
title	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_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_sort	gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using exphuntersuite
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/35510445a6824f5eb37caeaab2b029f1
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Gene expression analysis method integration and co-expression module detection applied to rare glucide metabolism disorders using ExpHunterSuite

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