Overlapping enriched terms refer to a special function derived from the ‘Enrich’ method in MELODI Presto , for which we have leveraged their API for queries. In essence, this feature lets you explore the interconnections between two lists of search terms, such as exposures and outcomes.
The ‘Enrich’ function applies a standard 2x2 Fisher’s exact test. To illustrate, if a search like ‘Sleep duration’ leads to a result like ‘Sleep Apnea, Obstructive: PREDISPOSES: Hypertensive disease’, the method ll look at the specific count of this result (localCount), the total results from the search (localTotal), the frequency of this specific result in the database (globalCount), and the total number of results in the database (globalTotal). These values are inputted into a 2x2 contingency table, and then formulate an odds ratio and P-value using a two-sided alternative hypothesis .
The ‘Overlap’ function then comes into play. After testing all terms from both lists for enrichment, it identify elements that are common or ‘overlap’ between the two. An overlap is understood as instances where the result (‘object’) of a query from the first list (‘x’ queries) coincides with the subject of a query from the second list (‘y’ queries). In simpler terms, this feature is all about discovering shared or intersecting points between two sets of data (e.g., exposures and outcomes).
 Elsworth, Benjamin, and Tom R Gaunt. “MELODI Presto: a fast and agile tool to explore semantic triples derived from biomedical literature.” Bioinformatics (Oxford, England) vol. 37,4 (2021): 583-585. doi:10.1093/bioinformatics/btaa726