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Gilles Renand

dblp:276/0637 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › data integration
heterogeneous data integration
0.412020
Link-HD: a versatile framework to explore and integrate heterogeneous microbial communities · Bioinform. 2020
Bioinformatics and computational biology › computational microbiology
microbiome analysis
0.412020
Link-HD: a versatile framework to explore and integrate heterogeneous microbial communities · Bioinform. 2020
Bioinformatics and computational biology
metagenomics
0.112020
Link-HD: a versatile framework to explore and integrate heterogeneous microbial communities · Bioinform. 2020

Methods — techniques the papers use, named apart from their topics

variable selection · 0.4taxon-set enrichment analysis · 0.4multi-table ordination · 0.4
YearPublicationVenuePosition
2020 Link-HD: a versatile framework to explore and integrate heterogeneous microbial communities
abstract
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.
Laura M. Zingaretti, Gilles Renand, Diego P. Morgavi, Yuliaxis Ramayo-Caldas
Bioinform.2