Repeatability of published microarray gene expression analyses View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2009-02

AUTHORS

John P A Ioannidis, David B Allison, Catherine A Ball, Issa Coulibaly, Xiangqin Cui, Aedín C Culhane, Mario Falchi, Cesare Furlanello, Laurence Game, Giuseppe Jurman, Jon Mangion, Tapan Mehta, Michael Nitzberg, Grier P Page, Enrico Petretto, Vera van Noort

ABSTRACT

Given the complexity of microarray-based gene expression studies, guidelines encourage transparent design and public data availability. Several journals require public data deposition and several public databases exist. However, not all data are publicly available, and even when available, it is unknown whether the published results are reproducible by independent scientists. Here we evaluated the replication of data analyses in 18 articles on microarray-based gene expression profiling published in Nature Genetics in 2005-2006. One table or figure from each article was independently evaluated by two teams of analysts. We reproduced two analyses in principle and six partially or with some discrepancies; ten could not be reproduced. The main reason for failure to reproduce was data unavailability, and discrepancies were mostly due to incomplete data annotation or specification of data processing and analysis. Repeatability of published microarray studies is apparently limited. More strict publication rules enforcing public data availability and explicit description of data processing and analysis should be considered. More... »

PAGES

149-155

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    URI

    http://scigraph.springernature.com/pub.10.1038/ng.295

    DOI

    http://dx.doi.org/10.1038/ng.295

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1051471999

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/19174838


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