## OmicKriging: Poly-Omic Prediction of Complex TRaits

It provides functions to generate a correlation matrix
from a genetic dataset and to use this matrix to predict the phenotype of an
individual by using the phenotypes of the remaining individuals through
kriging. Kriging is a geostatistical method for optimal prediction or best
unbiased linear prediction. It consists of predicting the value of a
variable at an unobserved location as a weighted sum of the variable at
observed locations. Intuitively, it works as a reverse linear regression:
instead of computing correlation (univariate regression coefficients are
simply scaled correlation) between a dependent variable Y and independent
variables X, it uses known correlation between X and Y to predict Y.

Version: |
1.4.0 |

Depends: |
R (≥ 2.15.1), doParallel |

Imports: |
ROCR, irlba, parallel, foreach |

Published: |
2016-03-08 |

Author: |
Hae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily
Trubetskoy |

Maintainer: |
Hae Kyung Im <haky at uchicago.edu> |

BugReports: |
NA |

License: |
GPL (≥ 3) |

URL: |
NA |

NeedsCompilation: |
no |

Materials: |
README |

CRAN checks: |
OmicKriging results |

#### Downloads: