MORPHIN: a web tool for human disease research by projecting model organism biology onto a human integrated gene network

Abstract

Despite recent advances in human genetics, model organisms are indispensable for human disease research. Most human disease pathways are evolutionally conserved among other species, where they may phenocopy the human condition or be associated with seemingly unrelated phenotypes. Much of the known gene-to-phenotype association information is distributed across diverse databases, growing rapidly due to new experimental techniques. Accessible bioinformatics tools will therefore facilitate translation of discoveries from model organisms into human disease biology. Here, we present a web-based discovery tool for human disease studies, MORPHIN (model organisms projected on a human integrated gene network), which prioritizes the most relevant human diseases for a given set of model organism genes, potentially highlighting new model systems for human diseases and providing context to model organism studies. Conceptually, MORPHIN investigates human diseases by an orthology-based projection of a set of model organism genes onto a genome-scale human gene network. MORPHIN then prioritizes human diseases by relevance to the projected model organism genes using two distinct methods: a conventional overlap-based gene set enrichment analysis and a network-based measure of closeness between the query and disease gene sets capable of detecting associations undetectable by the conventional overlap-based methods. MORPHIN is freely accessible at http://www.inetbio.org/morphin.

Figure 1.

The overall design of the MORPHIN web server. Once a user submits a set of query genes for one of nine supported model organisms, MORPHIN performs the following analyses: MORPHIN first identifies human orthologs of the submitted model organism genes using INPARANOID (11). MORPHIN then searches for related human disease pathways to the query genes using Fisher's exact test (12) and RIDDLE (10). Third, for each significantly associated human disease pathways, MORPHIN displays the gene network between the query genes and disease genes by HumanNet links. Finally, MORPHIN prioritizes the query genes for the relevant human disease.

Figure 2.

Screenshots of MORPHIN resulting from a query using six worm genes modulating dauer induction. (A) A table of human orthologs for the submitted six worm genes. The third column shows the in-paralog confidence score for each ortholog. (B) A table of significantly associated human disease pathways ranked by the Fisher's exact test. The P-value represents the statistical significance by Fisher's exact test; the q-value represents the adjusted significance for multiple hypotheses test;

Figure 3.

Networks between human orthologs of the 11 worm genes linked to an increased number of fat associated organelles (query genes) and human homocystinuria (A) or hyperhomocysteinemia (B) genes (disease pathway genes). Despite no overlap between query genes and disease pathway genes (there is no box for overlap genes) RIDDLE detected statistically significant association between them by using HumanNet-based connections between genes from the two gene sets.

Figure 4.

MORPHIN improves identification of human diseases associated with four model organism pathways. The reciprocal of the rank of the matching subset of reference gene-OMIM disease pairs is shown for Fisher's exact test (FET) and MORPHIN in mouse (A), worm (B), fly (C) and zebrafish (D). MORPHIN identified 85.2%, 67.1%, 8.8% and 5.3% of the reference gene-OMIM pairs, while the conventional FET method identified 81.8%, 55.0%, 0.0% and 2.0% in the top 10 ranks for mouse, worm, fly and zebrafish, respectively. The RIDDLE algorithm improved the performance of MORPHIN by 3.4pp, 12.1pp, 8.8pp and 3.3pp in the four species, respectively.