EsMeCaTa: Estimating metabolic capabilities from taxonomic affiliations
FRIOUX, Clémence
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
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Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
FRIOUX, Clémence
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
< Leer menos
Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE]
Idioma
en
Document de travail - Pré-publication
Resumen en inglés
Predicting the functional potential of microorganisms in environmental samples from cultivation-independent techniques is a major challenge. A persistent difficulty lies in associating taxonomic profiles obtained from ...Leer más >
Predicting the functional potential of microorganisms in environmental samples from cultivation-independent techniques is a major challenge. A persistent difficulty lies in associating taxonomic profiles obtained from metabarcoding experiment with accurate functional profiles, particularly for poorly-resolved taxonomic groups. In this paper, we present EsMeCaTa a python package predicting shared proteins from taxonomic affiliations. EsMeCaTa relies on the UniProt database to retrieve the public proteomes associated with a taxon and then uses MMseqs2 in order to compute the set of proteins shared in the taxon. Finally, EsMeCaTa extracts the functional annotations of these proteins to provide an accurate estimate of the functional potential associated to taxonomic affiliations.< Leer menos
Proyecto ANR
Deciphering plant-microbiome interactions to enhance crop defense to bioagressors - ANR-20-PCPA-0004
Orígen
Importado de HalCentros de investigación