ArticleiScience2024
Analyzing sex imbalance in EGA and dbGaP biological databases: Recommendations for better practices.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Large-scale automated detection reveals pervasive sex imbalance in biomedical research.bioRxiv : the preprint server for biology · 2026Article
- Sex-specific transcriptome similarity networks elucidate comorbidity relationships.Communications medicine · 2025Article
- Accurate sex prediction of cisgender and transgender individuals without brain size bias.Scientific reports · 2023Article
- Sex and Gender Dimensions in Hazard and Risk Assessment of Engineered Nanomaterials.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnologyReview
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Precision medicine aims at tailoring treatments to individual patient's characteristics. In this regard, recognizing the significance of sex and gender becomes indispensable for meeting the distinct healthcare needs of diverse populations. To this end, continuing a trend of improving data quality observed since 2014, the European Genome-phenome Archive (EGA) established a policy in 2018 that mandates data providers to declare the sex of donor samples, aiming to enhance data accuracy and prevent imbalance in sex classification. We analyzed sex classification imbalance in human data from EGA and the U.S. counterpart, the database of genotypes and phenotypes (dbGaP). Our findings show a significant decrease in samples classified as unknown in EGA, potentially promoting better sex reporting during data collection. Based on our findings, we raise awareness of sample imbalance problems and provide a list of recommendations for enhancing biomedical research practices.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.