pomRelate is a static, client-side tool for cross-species gene analysis in
model organisms, centered on Schizosaccharomyces pombe.
It enables researchers to seamlessly map orthologs, visualize protein-protein interaction (PPI) networks,
perform functional enrichment analysis (GO & KEGG), and explore phylogenetic relationships through
pre-computed gene trees across 7 model organisms — all entirely in the browser with no backend server required.
Orthology Mapping
Orthologs are mapped using NOG-based orthology from STRING v12.0 at the Eukaryota
level, with alias-based name matching as fallback.
PPI Networks
Interaction data is sourced from STRING v12.0. The network visualization uses a
force-directed layout to cluster related proteins. Hub genes are identified based on degree
centrality.
Enrichment Analysis
GO and KEGG enrichment is performed using a Fisher's Exact Test (Hypergeometric test) with
Benjamini-Hochberg FDR correction. Background sets are species-specific genome-wide annotations.
Hierarchical Clustering (Tree View)
Enriched terms can be clustered into a dendrogram based on gene set overlap. The pairwise
Jaccard distance (1 − |A ∩ B| / |A ∪ B|) measures how similar two terms'
gene sets are. UPGMA agglomerative clustering groups terms with the most shared genes
together. The resulting tree helps identify functional modules — clusters of related biological
processes enriched in your gene set.
Phylogeny Analysis
Gene trees are derived from eggNOG v7 pre-computed protein family phylogenies
(Hernández-Plaza et al., 2026), pruned to model organism species. Orthologous group (NOG)
assignments are obtained from STRING v12.0 hierarchical orthology data at the Eukaryota
level (taxonomy ID 2759). eggNOG v7 tree tip labels use the same taxid.UniProtID format
as STRING, enabling direct protein ID matching. Trees are rendered as rectangular cladograms with
query genes highlighted in red and target species genes in blue. Hover over any leaf node to see
species, gene IDs, orthogroup, branch length, and links to eggNOG, STRING, and UniProt.
References
Szklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A. L., Fang, T., Doncheva, N. T., Pyysalo, S., Bork, P., Jensen, L. J., & von Mering, C. (2023). The STRING database in 2023: Protein–protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Research, 51(D1), D483–D489. https://doi.org/10.1093/nar/gkac1000
Kanehisa, M., Furumichi, M., Sato, Y., Kawashima, M., & Ishiguro-Watanabe, M. (2023). KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Research, 51(D1), D587–D592. https://doi.org/10.1093/nar/gkac963
The Gene Ontology Consortium. (2023). The Gene Ontology knowledgebase in 2023. Genetics, 224(1), iyad031. https://doi.org/10.1093/genetics/iyad031
Amos, B., Aurrecoechea, C., Barber, M., Baber, P., Blevins, A. S., Brunk, B. P., Caler, E., Fischer, S., Harb, O. S., Kissinger, J. C., Li, W., Pennington, C., Pinney, D. F., Roos, D. S., & Stoeckert, C. J. (2022). VEuPathDB: The eukaryotic pathogen, vector and host bioinformatics resource center. Nucleic Acids Research, 50(D1), D898–D911. https://doi.org/10.1093/nar/gkab929
Hernández-Plaza, A., Szklarczyk, D., Coelho, L. P., Mathieson, M., Kuhn, M., Forslund, S. K., Jensen, L. J., von Mering, C., & Bork, P. (2026). eggNOG v7: phylogeny-based orthology predictions and functional annotations. Nucleic Acids Research, 54(D1), D402. https://doi.org/10.1093/nar/gkaf1249