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Variable selection in microbiome compositional data analysis

Author
Susin, A.; Calle, M.; Wang, Y.; Le Cao, K.
Type of activity
Journal article
Journal
NAR Genomics and Bioinformatics
Date of publication
2020-06-01
Volume
2
Number
2
First page
lqaa0297/1
Last page
lqaa029/14
DOI
10.1093/nargab/lqaa029
Repository
http://hdl.handle.net/2117/340287 Open in new window
URL
https://academic.oup.com/nargab/article/2/2/lqaa029/5836692 Open in new window
Abstract
Though variable selection is one of the most relevant tasks in microbiome analysis, e.g. for the identification of microbial signatures, many studies still rely on methods that ignore the compositional nature of microbiome data. The applicability of compositional data analysis methods has been hampered by the availability of software and the difficulty in interpreting their results. This work is focused on three methods for variable selection that acknowledge the compositional structure of micro...
Citation
Susin, A. [et al.]. Variable selection in microbiome compositional data analysis. "NAR Genomics and Bioinformatics", 1 Juny 2020, vol. 2, núm. 2, p. lqaa0297/1-lqaa029/14.
Group of research
ViRVIG - Visualisation, Virtual Reality and Graphic Interaction Research Group

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