The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models Academic Article uri icon

Overview

MeSH Major

  • Liver Diseases
  • Lung Diseases
  • Neoplasms
  • Oligonucleotide Array Sequence Analysis

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.

authors

publication date

  • August 2010

Research

keywords

  • Academic Article

Identity

Language

  • eng

PubMed Central ID

  • PMC3315840

Digital Object Identifier (DOI)

  • 10.1038/nbt.1665

PubMed ID

  • 20676074

Additional Document Info

start page

  • 827

end page

  • 38

volume

  • 28

number

  • 8