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MultiBaC: A strategy to remove batch effects between different omic data types

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MultiBaC: A strategy to remove batch effects between different omic data types

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Ugidos, M.; Tarazona Campos, S.; Prats-Montalbán, JM.; Ferrer, A.; Conesa, A. (2020). MultiBaC: A strategy to remove batch effects between different omic data types. Statistical Methods in Medical Research. 29(10):2851-2864. https://doi.org/10.1177/0962280220907365

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/163188

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Title: MultiBaC: A strategy to remove batch effects between different omic data types
Author: Ugidos, Manuel Tarazona Campos, Sonia Prats-Montalbán, José Manuel Ferrer, Alberto Conesa, Ana
UPV Unit: Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Issued date:
Abstract:
[EN] Diversity of omic technologies has expanded in the last years together with the number of omic data integration strategies. However, multiomic data generation is costly, and many research groups cannot afford research ...[+]
Subjects: Batch effect correction , Multiomic integration , Multivariate methods , Biostatistics
Copyrigths: Reserva de todos los derechos
Source:
Statistical Methods in Medical Research. (issn: 0962-2802 )
DOI: 10.1177/0962280220907365
Publisher:
SAGE Publications
Publisher version: https://doi.org/10.1177/0962280220907365
Project ID:
info:eu-repo/grantAgreement/GVA//PROMETEO%2F2016%2F093/ES/The Next Systems Biology: desarrollo de métodos estadísticos para la biología de sistemas multiómica/
Thanks:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work is part of a research project that is totally funded by Conselleria d'Educacio, ...[+]
Type: Artículo

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