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Harmonization of quality metrics and power calculation in multi-omic studies

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Harmonization of quality metrics and power calculation in multi-omic studies

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dc.contributor.author Tarazona Campos, Sonia es_ES
dc.contributor.author Balzano-Nogueira, Leandro es_ES
dc.contributor.author Gómez-Cabrero, David es_ES
dc.contributor.author Schmidt, Andreas es_ES
dc.contributor.author Imhof, Axel es_ES
dc.contributor.author Hankemeier, Thomas es_ES
dc.contributor.author Tegnér, Jesper es_ES
dc.contributor.author Westerhuis, Johan A. es_ES
dc.contributor.author Conesa, Ana es_ES
dc.date.accessioned 2021-02-25T04:49:37Z
dc.date.available 2021-02-25T04:49:37Z
dc.date.issued 2020-06-18 es_ES
dc.identifier.issn 2041-1723 es_ES
dc.identifier.uri http://hdl.handle.net/10251/162371
dc.description.abstract [EN] Multi-omic studies combine measurements at different molecular levels to build comprehensive models of cellular systems. The success of a multi-omic data analysis strategy depends largely on the adoption of adequate experimental designs, and on the quality of the measurements provided by the different omic platforms. However, the field lacks a comparative description of performance parameters across omic technologies and a formulation for experimental design in multi-omic data scenarios. Here, we propose a set of harmonized Figures of Merit (FoM) as quality descriptors applicable to different omic data types. Employing this information, we formulate the MultiPower method to estimate and assess the optimal sample size in a multi-omics experiment. MultiPower supports different experimental settings, data types and sample sizes, and includes graphical for experimental design decision-making. MultiPower is complemented with MultiML, an algorithm to estimate sample size for machine learning classification problems based on multi-omic data. es_ES
dc.description.sponsorship This work has been funded by FP7 STATegra project agreement 306000 and Spanish MINECO grant BIO2012-40244. In addition, work in the Imhof lab has been funded by the (DFG; CIPSM and SFB1064). The work of L.B.-N. has been funded by the University of Florida Startup funds. es_ES
dc.language Inglés es_ES
dc.publisher Nature Publishing Group es_ES
dc.relation.ispartof Nature Communications es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Harmonization of quality metrics and power calculation in multi-omic studies es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1038/s41467-020-16937-8 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/306000/EU/User-driven Development of Statistical Methods for Experimental Planning, Data Gathering, and Integrative Analysis of Next Generation Sequencing, Proteomics and Metabolomics data/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//BIO2012-40244/ES/DESARROLLO DE RECURSOS COMPUTACIONALES PARA LA CARACTERIZACION Y ANOTACION FUNCIONAL DE ARN NO CODIFICANTE./ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/DFG//SFB 1064/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Tarazona Campos, S.; Balzano-Nogueira, L.; Gómez-Cabrero, D.; Schmidt, A.; Imhof, A.; Hankemeier, T.; Tegnér, J.... (2020). Harmonization of quality metrics and power calculation in multi-omic studies. Nature Communications. 11(1):1-13. https://doi.org/10.1038/s41467-020-16937-8 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1038/s41467-020-16937-8 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 13 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.description.issue 1 es_ES
dc.identifier.pmid 32555183 es_ES
dc.identifier.pmcid PMC7303201 es_ES
dc.relation.pasarela S\414882 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder University of Florida es_ES
dc.contributor.funder Deutsche Forschungsgemeinschaft es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Center for Integrated Protein Science Munich es_ES
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