Package: OmicKriging
Type: Package
Title: OmicKriging for Phenotypic Prediction
Version: 1.0
Date: 2013-03-08
Author: Hae Kyung Im, Heather E. Wheeler
Maintainer: Hae Kyung Im <haky@uchicago.edu>
Description: This package provides functions to generate correlation
matrices from SNP, gene expression, methylation or other
'omics' datasets and to use these matrices 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.
License: GPL (>= 3)
Depends: R(>= 2.10.0)
Packaged: 2013-03-08 16:32:07 UTC; hwheeler
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-03-09 05:29:37

Package: OmicKriging
Type: Package
Title: OmicKriging for Phenotypic Prediction
Version: 1.1
Date: 2013-09-26
Author: Hae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily
Trubetskoy
Maintainer: Hae Kyung Im <haky@uchicago.edu>
Description: 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.
License: GPL (>= 3)
Depends: R(>= 2.15.1), SNPRelate, doMC
Imports: ROCR, inline, gdsfmt, irlba, Rcpp, RcppEigen
Collate: 'input_pheno_GT.R' 'omic_KRIGR.R' 'correlation_matrices.R'
Packaged: 2014-01-22 16:19:12 UTC; vasya
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-02-01 07:59:52