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Scientific article
English

Network principal component analysis: a versatile tool for the investigation of multigroup and multiblock datasets

Published inBioinformatics
Publication date2020
Abstract

Complex data structures composed of different groups of observations and blocks of variables are increasingly collected in many domains, including metabolomics. Analysing these high-dimensional data constitutes a challenge, and the objective of this article is to present an original multivariate method capable of explicitly taking into account links between data tables when they involve the same observations and/or variables. For that purpose, an extension of standard principal component analysis called NetPCA was developed.

Citation (ISO format)
CODESIDO SANCHEZ, Santiago et al. Network principal component analysis: a versatile tool for the investigation of multigroup and multiblock datasets. In: Bioinformatics, 2020. doi: 10.1093/bioinformatics/btaa954
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ISSN of the journal1367-4803
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