ArticleLaboratory investigation; a journal of technical methods and pathology2019
Trends in the characteristics of human functional genomic data on the gene expression omnibus, 2001-2017.
Article in Laboratory investigation; a journal of technical methods and pathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
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- Towards machine learning fairness in classifying multicategory causes of deaths in colorectal or lung cancer patients.Briefings in bioinformatics · 2025Article
- Digital and Artificial Intelligence-based Pathology: Not for Every Laboratory - A Mini-review on the Benefits and Pitfalls of Its Implementation.Journal of clinical and translational pathology · 2025Article
- Normalization and Selecting Non-Differentially Expressed Genes Improve Machine Learning Modelling of Cross-Platform Transcriptomic Data.Transactions on artificial intelligence · 2025Article
- Sparassis latifolia and exercise training as complementary medicine mitigated the 5-fluorouracil potent side effects in mice with colorectal cancer: bioinformatics approaches, novel monitoring pathological metrics, screening signatures, and innovative management tactic.Cancer cell international · 2024Article
- The Challenges and Opportunities of Translational Pathology.Journal of clinical and translational pathology · 2022Article
- Multimetric feature selection for analyzing multicategory outcomes of colorectal cancer: random forest and multinomial logistic regression models.Laboratory investigation; a journal of technical methods and pathology · 2022Article
- Performance and efficiency of machine learning algorithms for analyzing rectangular biomedical data.Laboratory investigation; a journal of technical methods and pathology · 2021Article
- Statistics and pitfalls of trend analysis in cancer research: a review focused on statistical packages.Journal of Cancer · 2020Review
- Advances in the Clinical Application of High-throughput Proteomics.Exploratory research and hypothesis in medicineArticle
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Authors and funding
2 authors.
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Abstract
The gene expression omnibus (GEO) is the world's largest public repository of functional genomic data. Despite its broad use in secondary genomic analyses, the temporal trends in the characteristics of genomic data on GEO, including experimental procedures, geographic origin, funder(s), and related disease, have not been examined. We identified 75,376 Series deposited to the GEO during 2001-2017 and built a database of all human genomic data (39,076 Series, 51.8% of all Series). Using the associated publications, we obtained funding information and identified the related disease area. Of the Series with classified disease areas, the two most common were cancer (n = 12,688, 32.5%) and immunologic diseases (n = 2,393, 6.1%), while the percentages of all other disease areas were below 5%, including neurological diseases (n = 1733, 4.4%), infectious diseases (n = 1225, 3.1%), diabetes (n = 828, 2.1%), and cardiovascular diseases (n = 299, 0.8%). In recent years, there has been a significant increase in the use of high-throughput sequencing (HTS), protein array and multiple-platform technologies, as well as in the proportion of North American deposits. Compared to those from other regions, North American deposits appeared to lead the shift from array-based to HTS technologies (odds ratio [OR], 95% confidence intervals [CI] = 3.39, 3.23-3.55, P = 9.40E-323), and were less likely to focus on a major disease area (OR = 0.64, 95% CI: 0.61-0.67, P = 5.02E-107), suggesting a greater emphasis on basic science in North America. Furthermore, the Series utilizing HTS were less likely to be disease-classified compared to other technologies (OR = 0.39, 95% CI: 0.37-0.41, P = 1.00E-322), suggesting a preferential use or adoption of HTS in basic science settings. Finally, funding from the NHGRI, NCI, NIEHS, and NCCR resulted in a higher number of GEO Series per grant than other NIH institutes, demonstrating different preferences on genomic studies among awardees of NIH institutes. Our findings demonstrate geographic, technological, and funding disparities in the trends of GEO deposit characteristics.
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