ArticleNature biotechnology2010
The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.
Article in Nature biotechnology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 447 papers, 1 of them a synthesis that pooled it.
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Who cites it
447 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- HABiC: an algorithm based on the exact computation of the Kantorovich-Rubinstein optimizer for binary classification in transcriptomics.Bioinformatics (Oxford, England) · 2025Article
- Individualized dynamic risk assessment and treatment selection for multiple myeloma.British journal of cancer · 2025Article
387 more citing papers are in PubMed but not listed here.
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Funding
Abstract
Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.
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