Functional Annotation with EggNOG Mapper


EggNOG-mapper is a tool for fast functional annotation of novel sequences (genes or proteins) using precomputed eggNOG-based orthology assignments. Obvious examples include the annotation of novel genomes, transcriptomes or even metagenomic gene catalogs. The use of orthology predictions for functional annotation is considered more precise than traditional homology searches, as it avoids transferring annotations from paralogs (duplicate genes with a higher chance of being involved in functional divergence).

Details and methodology about the tool and its database are best explained on their website: .

EggNOG-mapper can be found under Functional Analysis → EggNOG Annotation → EggNOG Mapper. The wizard allows to select the parameters for the functional annotation (figure 1).

Wizard Page

  • Target Orthologs: Define what type of orthologs should be used for functional transfer.

  • GO Evidence: Define what type of GO terms should be used for annotation:

    • experimental = Use only terms inferred from experimental evidence.

    • non-electronic = Use only non-electronically curated terms.

Figure 1. EggNOG Mapper wizard page.


The result table summarizes all annotations that could be transferred with EggNOG Mapper. Besides ordering and filtering, the context menu allows taking a closer look at certain results (figure 2). This annotation process also generates a Summary Report with information about the total number of GOs, the COG categories and the orthologous groups distribution.

Figure 2. EggNOG results table.

The annotation details (right-click on an annotated sequence → Show Annotation Details) provide link outs where possible and give detailed information about annotated GOs (figure 3).

Figure 3. Annotation details.


Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Jaime Huerta-Cepas, Damian Szklarczyk, Lars Juhl Jensen, Christian von Mering and Peer Bork. Submitted (2016).

eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Jaime Huerta-Cepas, Damian Szklarczyk, Kristoffer Forslund, Helen Cook, Davide Heller, Mathias C. Walter, Thomas Rattei, Daniel R. Mende, Shinichi Sunagawa, Michael Kuhn, Lars Juhl Jensen, Christian von Mering, and Peer Bork. Nucl. Acids Res. (04 January 2016) 44 (D1): D286-D293. doi: 10.1093/nar/gkv1248