Efficient computation of significance levels for multiple associations in large studies of correlated data, including genomewide association studies.

@article{Dudbridge2004EfficientCO,
  title={Efficient computation of significance levels for multiple associations in large studies of correlated data, including genomewide association studies.},
  author={Frank Dudbridge and Bobby P. C. Koeleman},
  journal={American journal of human genetics},
  year={2004},
  volume={75 3},
  pages={424-35}
}
Large exploratory studies, including candidate-gene-association testing, genomewide linkage-disequilibrium scans, and array-expression experiments, are becoming increasingly common. A serious problem for such studies is that statistical power is compromised by the need to control the false-positive rate for a large family of tests. Because multiple true associations are anticipated, methods have been proposed that combine evidence from the most significant tests, as a more powerful alternative… CONTINUE READING

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