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DExMA: An R Package for Performing Gene Expression Meta-Analysis with Missing Genes

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  • Juan Antonio Villatoro-García

    (Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain
    Bioinformatics Unit, Centre for Genomics and Oncological Research Pfizer/University of Granada/Andalusian Regional Government, 18016 Granada, Spain)

  • Jordi Martorell-Marugán

    (Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain
    Bioinformatics Unit, Centre for Genomics and Oncological Research Pfizer/University of Granada/Andalusian Regional Government, 18016 Granada, Spain
    Data Science for Heath Research Unit, Fondazione Bruno Kessler, 38123 Trento, Italy)

  • Daniel Toro-Domínguez

    (Medical Genomics, Centre for Genomics and Oncological Research Pfizer/University of Granada/Andalusian Regional Government, 18016 Granada, Spain)

  • Yolanda Román-Montoya

    (Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain)

  • Pedro Femia

    (Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain)

  • Pedro Carmona-Sáez

    (Department of Statistics and Operational Research, University of Granada, 18071 Granada, Spain
    Bioinformatics Unit, Centre for Genomics and Oncological Research Pfizer/University of Granada/Andalusian Regional Government, 18016 Granada, Spain)

Abstract

Meta-analysis techniques allow researchers to jointly analyse different studies to determine common effects. In the field of transcriptomics, these methods have gained popularity in recent years due to the increasing number of datasets that are available in public repositories. Despite this, there is a limited number of statistical software packages that implement proper meta-analysis functionalities for this type of data. This article describes DExMA, an R package that provides a set of functions for performing gene expression meta-analyses, from data downloading to results visualization. Additionally, we implemented functions to control the number of missing genes, which can be a major issue when comparing studies generated with different analytical platforms. DExMA is freely available in the Bioconductor repository.

Suggested Citation

  • Juan Antonio Villatoro-García & Jordi Martorell-Marugán & Daniel Toro-Domínguez & Yolanda Román-Montoya & Pedro Femia & Pedro Carmona-Sáez, 2022. "DExMA: An R Package for Performing Gene Expression Meta-Analysis with Missing Genes," Mathematics, MDPI, vol. 10(18), pages 1-15, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:18:p:3376-:d:917305
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    References listed on IDEAS

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    2. N A Heard & P Rubin-Delanchy, 2018. "Choosing between methods of combining $p$-values," Biometrika, Biometrika Trust, vol. 105(1), pages 239-246.
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