## ldDesign: Design of experiments for detection of linkage disequilibrium

R package for design of experiments for design of
genome-wide association studies. Version 2 incorporating
quantitative traits and case-control studies. The Bayes factor
should be chosen large enough to give respectable posterior
odds. This requires Bayes factors of the order of 10^6 in
genome-wide association studies where prior odds are low.
Sample sizes needed to get this strength of evidence are
substantially higher than those from traditional power
calculations. The corresponding threshold for p-values is
substantially lower than commonly used. For quantitative
traits ldDesign uses an existing deterministic power
calculation for detection of linkage disequilibrium between a
bi-allelic QTL and a bi-allelic marker, together with the
Spiegelhalter and Smith Bayes factor to generate designs with
power to detect effects with a given Bayes factor. For case-
control studies an asymptotic approximate Bayes factor is used
to derive an analytical power calculation in dominant,
recessive, additive and general genetic models.

Version: |
2.0-1 |

Suggests: |
nlme (≥ 3.1.0) |

Published: |
2012-03-26 |

Author: |
Rod Ball |

Maintainer: |
ORPHANED |

License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |

URL: |
mailto:rod.ball@scionresearch.com www.scionresearch.com/ |

NeedsCompilation: |
no |

In views: |
ExperimentalDesign, Genetics |

CRAN checks: |
ldDesign results |

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