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Letunic, I.

Publications and source records attributed to Letunic, I..

2 recordsLinked to original sources

Refined Enterotyping Reveals Dysbiosis in Global Fecal Metagenomes

BackgroundEnterotypes describe human fecal microbiomes grouped by similarity into clusters of microbial community composition, often associated with disease, medications, diet, and lifestyle. Numbers and determinants of enterotypes have been derived by diverse frameworks and applied to cohorts that often lack diversity or inter-cohort comparability. ResultsTo overcome these limitations, we selected 16,772 fecal metagenomes collected from 38 countries to revisit the enterotypes using state-of-the-art fuzzy clustering and found robust clustering regardless of underlying taxonomy, consistent with previous findings. Quantifying the strength of enterotype classifications enriched the enterotype landscape, also reflecting some continuity of microbial compositions. As the classification strength was associated with the patients health status, we established an "Enterotype Dysbiosis Score" (EDS) as a latent covariate for various diseases. ConclusionThis global study confirms the enterotypes, reveals a dysbiosis signal within the enterotype landscape, and enables robust classification of metagenomes with an online "Enterotyper" tool, allowing reproducible analysis in future studies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/607711v3_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1611a2org.highwire.dtl.DTLVardef@dfbb57org.highwire.dtl.DTLVardef@848ac0org.highwire.dtl.DTLVardef@1b15808_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale

Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows: (i) de novo gene prediction from raw contigs, (ii) built-in pairwise orthology prediction, (iii) fast protein domain discovery, and (iv) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.

bioinformatics↗