PT - JOURNAL ARTICLE AU - David Angeles-Albores AU - Raymond YN Lee AU - Juancarlos Chan AU - Paul W Sternberg TI - Phenotype and gene ontology enrichment as guides for disease modeling in <em>C. elegans</em> AID - 10.1101/106369 DP - 2017 Jan 01 TA - bioRxiv PG - 106369 4099 - http://biorxiv.org/content/early/2017/02/07/106369.short 4100 - http://biorxiv.org/content/early/2017/02/07/106369.full AB - Genome-wide experiments have the capacity to generate massive amounts of unbiased data about an organism. In order to interpret this data, dimensionality reduction techniques are required. One approach is to annotate genes using controlled languages and to test experimental datasets for term enrichment using probabilistic methods. Although gene, phenotype and anatomy ontologies exist for C. elegans, no unified software offers enrichment analyses of all the ontologies using the same methodology. Here, we present the WormBase Enrichment Suite, which offers users the ability to test all nematode ontologies simultaneously. We show that the WormBase Enrichment Suite provides valuable insight into different biological problems. Briefly, we show that phenotype enrichment analysis (PEA) can help researchers identify disease phenologs, phenotypes that are homologous across species, which can inform disease modeling in C. elegans. The WormBase Enrichment Suite analysis can also shed light on RNA-seq datasets by showing what molecular functions are enriched, which phenotypes these functions are implicated in and what tissues are overrepresented in the dataset. Finally, we explore the phenotype-anatomy relationship, showing that a small subset of highly specific tissues are disproportionately likely to cause an Egl phenotype, but inferring tissue expression from an Egl phenotype is limited to the largest tissues.