An automated identification and analysis of ontological terms in gastrointestinal diseases and nutrition-related literature provides useful insights
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Abstract
With an unprecedented growth in the biomedical literature, keeping up to date with the new developments presents an immense challenge. Publications are often studied in isolation of the established literature, with interpretation being subjective and often introducing human bias. With ontology-driven annotation of biomedical data gaining popularity in recent years and online databases offering metatags with rich textual information, it is now possible to automatically text-mine ontological terms and complement the laborious task of manual management, interpretation, and analysis of the accumulated literature with downstream statistical analysis. In this paper, we have formulated an automated workflow through which we have identified ontological information, including nutrition-related terms in PubMed abstracts (from 1991 until 2016) for two main types of Inflammatory Bowel Diseases: Crohn's Disease and Ulcerative Colitis; and two other gastrointestinal diseases, namely, Coeliac Disease and Irritable Bowel Syndrome. Our analysis reveals unique clustering patterns as well as spatial and temporal trends inherent to the considered gastrointestinal diseases in terms of literature that has been accumulated so far. Although automated interpretation cannot replace human judgement, the developed workflow shows promising results and can be a useful tool in systematic literature reviews. The workflow is available at https://github.com/KociOrges/pytag .
Cite this as
2018. An automated identification and analysis of ontological terms in gastrointestinal diseases and nutrition-related literature provides useful insights. PeerJ Preprints 6:e26869v1 https://doi.org/10.7287/peerj.preprints.26869v1note This preprint is not peer-reviewed. You may wish to reference the subsequent peer-reviewed version of this article.
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This is a submission to PeerJ for review.
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Supplemental Information
Differential expression analysis of nutrition-related terms between disease conditions
Four tables, Table_S1A (1991-1998), Table_S1B (1999-2004), Table_S1C (2005-2010), and Table_S1D (2011-2016) for differential expression analysis of nutrition-related terms between diseases using Kruskal-Wallis test. Only those terms are shown where the adjusted p-value (Padj) < 0.05. Mean expression indicates the mean document-based normalised frequency obtained for a specific term for each disease group. A post hoc pairwise Dunn’s comparison indicating significant differences between the groups is shown on the right half.
Differential expression analysis of nutrition-related terms between years
Four tables, Table_S2A (CCD), Table_S2B (CD), Table_S2C (IBS), and Table_S2D (UC) for differential expression analysis of nutrition-related terms between years using Kruskal-Wallis test. Only those terms are shown where the adjusted p-value (Padj) < 0.05. Mean expression indicates the mean document-based normalised frequency obtained for a specific term for each interval.
Additional Information
Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Orges Koci performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper.
Michael Logan analyzed the data, authored or reviewed drafts of the paper.
Vaios Svolos analyzed the data, authored or reviewed drafts of the paper.
Richard K. Russell contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper.
Konstantinos Gerasimidis conceived and designed the experiments, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper.
Umer Zeeshan Ijaz conceived and designed the experiments, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.
Data Deposition
The following information was supplied regarding data availability:
Funding
UZI is funded by NERC IRF NE/L011956/1. OK is supported by Nestle Industrial PhD Partnership with the University of Glasgow. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
