OmicKriging: OmicKriging for Phenotypic Prediction

This package 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: 1.3
Depends: R (≥ 2.15.1), doParallel
Imports: ROCR, irlba
Published: 2014-06-18
Author: Hae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily Trubetskoy
Maintainer: Hae Kyung Im <haky at uchicago.edu>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: NA
Materials: NA
CRAN checks: OmicKriging results

Downloads:

Reference manual: OmicKriging.pdf
Vignettes: Application Tutorial: OmicKriging
Package source: OmicKriging_1.3.tar.gz
Windows binaries: r-devel: OmicKriging_1.3.zip, r-release: OmicKriging_1.3.zip, r-oldrel: OmicKriging_1.3.zip
OS X Snow Leopard binaries: r-release: OmicKriging_1.3.tgz, r-oldrel: OmicKriging_1.3.tgz
OS X Mavericks binaries: r-release: OmicKriging_1.3.tgz
Old sources: OmicKriging archive