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

Ruiz-Serra, Victoria; Buslón, Nataly; Philippe, Olivier; Saby, Diego; Morales, María; Pontes, Camila; Muñoz Andirkó, Alejandro; Holliday, Gemma L.; Jene, Aina; Moldes, Mauricio; Rambla de Argila, Jordi; Valencia, Alfonso; Rementeria, María José; Cortés, Atia; Cirillo, Davide

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

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dc.contributor.author Ruiz-Serra, Victoria
dc.contributor.author Buslón, Nataly
dc.contributor.author Philippe, Olivier
dc.contributor.author Saby, Diego
dc.contributor.author Morales, María
dc.contributor.author Pontes, Camila
dc.contributor.author Muñoz Andirkó, Alejandro
dc.contributor.author Holliday, Gemma L.
dc.contributor.author Jene, Aina
dc.contributor.author Moldes, Mauricio
dc.contributor.author Rambla de Argila, Jordi
dc.contributor.author Valencia, Alfonso
dc.contributor.author Rementeria, María José
dc.contributor.author Cortés, Atia
dc.contributor.author Cirillo, Davide
dc.date.accessioned 2025-01-22T07:24:47Z
dc.date.available 2025-01-22T07:24:47Z
dc.date.issued 2024
dc.description.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.
dc.description.sponsorship The work has been supported by Bioinfo4Women through the project Excelencia Severo Ochoa (ref. CEX2021-001148-S) and the European Commission's Horizon 2020 Program, H2020-SC1-DTH-2018-2020, “iPC - individualizedPaediatricCure” (GA 826121). This work was conceptualized and prototyped during the BioHackathon Europe, organized and funded by the ELIXIR Hub in November 2021 in Barcelona. We thank the organizers for an opportunity to participate in such a productive and collaborative event. The authors would like to acknowledge the initiative Bioinfo4Women, Laura Rodríguez Navas (Spanish National Bioinformatics Institute, INB/ELIXIR-ES and Barcelona Supercomputing Center, BSC), Eva Alloza (Spanish National Bioinformatics Institute, INB/ELIXIR-ES and Barcelona Supercomputing Center, BSC), Francisco Garcia-Garcia (Prince Felipe Research Center, CIPF), Babita Singh (Center for Genomic Regulation, CRG), Ben Busby (DNANexus), and Michael Feolo (dbGaP) and the NCBI dbGaP support team. C.P. is supported by the fellowship Juan de La Cierva - Formación from the Spanish Ministry of Education and Science (ref. FJC2021-046655-I).
dc.format.mimetype application/pdf
dc.identifier.citation Ruiz-Serra V, Buslón N, Philippe OR, Saby D, Morales M, Pontes C, et al. Analyzing sex imbalance in EGA and dbGaP biological databases: Recommendations for better practices. iScience. 2024 Sep 23;27(10):110831. DOI: 10.1016/j.isci.2024.110831
dc.identifier.doi http://dx.doi.org/10.1016/j.isci.2024.110831
dc.identifier.issn 2589-0042
dc.identifier.uri http://hdl.handle.net/10230/69233
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartof iScience. 2024 Sep 23;27(10):110831
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/826121
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject.keyword Artificial intelligence
dc.subject.keyword Genomics
dc.subject.keyword Human genetics
dc.title Analyzing sex imbalance in EGA and dbGaP biological databases: Recommendations for better practices
dc.type info:eu-repo/semantics/article
dc.type.version info:eu-repo/semantics/publishedVersion

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