RT Journal Article SR Electronic T1 Phenotype and gene ontology enrichment as guides for disease modeling in C. elegans JF bioRxiv FD Cold Spring Harbor Laboratory SP 106369 DO 10.1101/106369 A1 David Angeles-Albores A1 Raymond YN Lee A1 Juancarlos Chan A1 Paul W Sternberg YR 2017 UL http://biorxiv.org/content/early/2017/02/07/106369.abstract 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.