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Título

Link-HD: a versatile framework to explore and integrate heterogeneous microbial communities

AutorZingaretti, Laura M. CSIC ORCID; Renand, Gilles; Morgavi, Diego P.; Ramayo-Caldas, Yuliaxis
Fecha de publicación2020
EditorOxford University Press
CitaciónBioinformatics 36(7): 2298-2299 (2020)
Resumen[Motivation]: We present Link-HD, an approach to integrate multiple datasets. Link-HD is a generalization of ‘Structuration des Tableaux A Trois Indices de la Statistique–Analyse Conjointe de Tableaux’, a family of methods designed to integrate information from heterogeneous data. Here, we extend the classical approach to deal with broader datasets (e.g. compositional data), methods for variable selection and taxon-set enrichment analysis.
[Results]: The methodology is demonstrated by integrating rumen microbial communities from cows for which methane yield (⁠CH4y⁠) was individually measured. Our approach reproduces the significant link between rumen microbiota structure and CH4 emission. When analyzing the TARA’s ocean data, Link-HD replicates published results, highlighting the relevance of temperature with members of phyla Proteobacteria on the structure and functionality of this ecosystem.
[Availability and implementation]: The source code, examples and a complete manual are freely available in GitHub https://github.com/lauzingaretti/LinkHD and in Bioconductor https://bioconductor.org/packages/release/bioc/html/LinkHD.html.
Versión del editorhttps://doi.org/10.1093/bioinformatics/btz862
URIhttp://hdl.handle.net/10261/220449
DOI10.1093/bioinformatics/btz862
ISSN1367-4803
E-ISSN1460-2059
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