Analyzing sex imbalance in EGA and dbGaP biological databases: Recommendations for better practices

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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Publication Details

Journal
iScience
Published
2024-09-23
DOI
https://doi.org/10.1016/j.isci.2024.110831
Citations
2
Primary Topic
Sex and Gender in Healthcare
Type
article
Field-Weighted Citation Impact
1.09

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article

Analyzing sex imbalance in EGA and dbGaP biological databases: Recommendations for better practices

Victoria Ruiz‐Serra, María José Rementeria, Alfonso Valencia, Mauricio Moldes et al.
2 citations
iScience
Sex and Gender in Healthcare
1.09
article

Analyzing sex imbalance in EGA and dbGaP biological databases: Recommendations for better practices

Victoria Ruiz‐Serra, María José Rementeria, Alfonso Valencia, Mauricio Moldes, Olivier Philippe, Jordi Rambla, Davide Cirillo, Aina Jené, Alejandro Muñoz Andirkó, Nataly Buslón, M. P. Morales, Diego Saby, Camila Pontes, Àtia Cortés, Gemma L. Holliday
article en
2 citations

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.

iScienceVol. 27(10)
Institució Catalana de Recerca i Estudis Avançats (ES), Universitat Pompeu Fabra (ES), Barcelona Supercomputing Center (ES), European Commission (BE), Medicines Discovery Catapult (GB), Ente Vasco de la Energía (ES), Centre for Genomic Regulation (ES), Universitat de Barcelona (ES), Universitat Politècnica de Catalunya (ES)
Ministerio de Ciencia, Innovación y Universidades, European Commission, Barcelona Supercomputing Center, Horizon 2020 Framework Programme
Gender equality
Openalex Percentile: Top 20%
Sex and Gender in Healthcare
1.09
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