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eggNOG v4.0: nested orthology inference across 3686 organisms
Sean Powell1, Kristoffer Forslund, Damian Szklarczyk
1European Molecular Biology Laboratory, Computational Biology Unit, Meyerhofstrasse 1, 69117 Heidelberg, Germany, University of Zurich and Swiss Institute of Bioinformatics, Institute of Molecular Life Sciences, Winterthurerstrasse 190, 8057 Zurich, Switzerland, Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109-5234, USA, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), C/Dr. Aiguader 88, 08003 Barcelona, Spain, Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain, CUBE-Division of Computational Systems Biology, Department of Microbiology and Ecosystem Science, University of Vienna, Althanstraße 14, 1090 Vienna, Austria, Institute of Biological, Environmental & Rural Sciences, Aberystwyth University, Penglais, Aberystwyth, Ceredigion, SY23 3FG, UK, Biotechnology Center, TU Dresden, 01062 Dresden, Germany, Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, 2200, Copenhagen N, Denmark and Max-Delbrück-Centre for Molecular Medicine, Robert-Rössle-Strasse 10, 13092 Berlin, Germany.
The eggNOG database (evolutionary للجينوميات orthologous groups) version 4 significantly expands its species coverage and enhances orthology assignment methods. This updated resource provides crucial tools for evolutionary and functional genomics research.
Area of Science:
- Genomics
- Bioinformatics
- Evolutionary Biology
Background:
- High-quality orthology assignment is essential for analyzing large 'omics datasets.
- Previous versions of eggNOG provided valuable orthologous groups but required expansion.
Purpose of the Study:
- To present the fourth version of the eggNOG database, enhancing orthology assignment and functional annotation.
- To expand the database's species coverage and improve analytical capabilities.
Main Methods:
- Derivation of nonsupervised orthologous groups (NOGs) from complete genomes.
- Application of a comprehensive characterization and analysis pipeline.
- Implementation of robust procedures for high-quality genome inclusion and quality control.
Main Results:
- Tripled species set to 3686 organisms, prioritizing high-quality genomes.
- Expanded taxonomic levels to 107, compared to 41 in eggNOGv3.
- Improved clustering, functional annotation, and tree-building procedures.
Conclusions:
- eggNOGv4 offers a significantly expanded and improved resource for orthology assignment.
- The database facilitates evolutionary and functional genomics studies through enhanced data and analytical tools.
- Users can access orthologous groups, alignments, trees, and functional annotations via web or bulk download.
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