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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> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | OmicKriging results |
| Reference manual: | OmicKriging.pdf |
| Vignettes: |
Application Tutorial: OmicKriging |
| 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 |
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