The CMVE software is available upon request from the authors.

BackgroundThe use of ontologies to control vocabulary and structure annotation has added value to genome-scale data, and contributed to the capture and re-use of knowledge across research domains. Gene Ontology (GO) is widely used to capture detailed expert knowledge in genomic-scale datasets and as a consequence has grown to contain many terms, making it unwieldy for many applications. To increase its ease of manipulation and efficiency of use, subsets called GO slims are often created by collapsing terms upward into more general, high-level terms relevant to a particular context. Creation of a GO slim currently requires manipulation and editing of GO by an expert (or community) familiar with both the ontology and the biological context. Decisions about which terms to include are necessarily subjective, and the creation process itself and subsequent curation are time-consuming and largely manual.ResultsHere we present an objective framework for generating customised ontology slims for specific annotated datasets, exploiting information latent in the structure of the ontology graph and in the annotation data. This framework combines ontology engineering approaches, and a data-driven algorithm that draws on graph and information theory. We illustrate this method by application to GO, generating GO slims at different information thresholds, characterising their depth of semantics and demonstrating the resulting gains in statistical power.ConclusionsOur GO slim creation pipeline is available for use in conjunction with any GO-annotated dataset, and creates dataset-specific, objectively defined slims. This method is fast and scalable for application to other biomedical ontologies.

http://pprowler.itee.uq.edu.au/NucImport

BACKGROUND & AIMS: Colorectal cancer (CRC) incidence at ages younger than 50 years is increasing, leading to proposals to lower the CRC screening initiation age to 45 years. Data on the effectiveness of CRC screening at ages 45-49 years are lacking. METHODS: We studied the association between undergoing colonoscopy at ages 45-49 or 50-54 years and CRC incidence in a retrospective population-based cohort study using Florida's linked Healthcare Cost and Utilization Project databases with mandated reporting from 2005 to 2017 and Cox models extended for time-varying exposure. RESULTS: Among 195,600 persons with and 2.6 million without exposure to colonoscopy at ages 45-49 years, 276 and 4844 developed CRC, resulting in CRC incidence rates of 20.8 (95% CI, 18.5-23.4) and 30.6 (95% CI, 29.8-31.5) per 100,000 person-years, respectively. Among 660,248 persons with and 2.4 million without exposure to colonoscopy at ages 50-54 years, 798 and 6757 developed CRC, resulting in CRC incidence rates of 19.0 (95% CI, 17.7-20.4) and 51.9 (95% CI, 50.7-53.1) per 100,000 person-years, respectively. The adjusted hazard ratios for incident CRC after undergoing compared with not undergoing colonoscopy were 0.50 (95% CI, 0.44-0.56) at ages 45-49 years and 0.32 (95% CI, 0.29-0.34) at ages 50-54 years. The results were similar for women and men (hazard ratio, 0.48; 95% CI, 0.40-0.57 and hazard ratio, 0.52; 95% CI, 0.43-0.62 at ages 45-49 years, and hazard ratio, 0.35; 95% CI, 0.31-0.39 and hazard ratio, 0.29; 95% CI, 0.26-0.32 at ages 50-54 years, respectively). CONCLUSIONS: Colonoscopy at ages 45-49 or 50-54 years was associated with substantial decreases in subsequent CRC incidence. These findings can inform screening guidelines.