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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
DOI:10.32614/CRAN.package.OmicKriging
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
Materials:README
CRAN checks:OmicKriging results

Documentation:

Reference manual:OmicKriging.html ,OmicKriging.pdf
Vignettes:Application Tutorial: OmicKriging (source,R code)

Downloads:

Package source: OmicKriging_1.4.0.tar.gz
Windows binaries: r-devel:OmicKriging_1.4.0.zip, r-release:OmicKriging_1.4.0.zip, r-oldrel:OmicKriging_1.4.0.zip
macOS binaries: r-release (arm64):OmicKriging_1.4.0.tgz, r-oldrel (arm64):OmicKriging_1.4.0.tgz, r-release (x86_64):OmicKriging_1.4.0.tgz, r-oldrel (x86_64):OmicKriging_1.4.0.tgz
Old sources: OmicKriging archive

Linking:

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