OmicKriging: Poly-Omic Prediction of Complex TRaits
Version 1.4.0

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.

Browse man pages Browse package API and functions Browse package files

AuthorHae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily Trubetskoy
Date of publication2016-03-08 00:12:43
MaintainerHae Kyung Im <haky@uchicago.edu>
LicenseGPL (>= 3)
Version1.4.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("OmicKriging")

Man pages

krigr_cross_validation: Multithreaded cross validation routine for Omic Kriging.
load_sample_data: Loads sample phenotype and covariate data into data frame.
make_GXM: Compute gene expression correlation matrix.
make_PCs_irlba: Run Principal Component Analysis (PCA) using the irlba...
make_PCs_svd: Run Principal Component Analysis (PCA) using base R svd()...
okriging: Run omic kriging on a set of correlation matrices and a given...
read_GRMBin: Read the GRM binary file.
write_GRMBin: Write GRM binary files.

Functions

krigr_cross_validation Man page Source code
load_sample_data Man page Source code
make_GXM Man page Source code
make_PCs_irlba Man page Source code
make_PCs_svd Man page Source code
okriging Man page Source code
read_GRMBin Man page Source code
write_GRMBin Man page Source code

Files

inst
inst/doc
inst/doc/OmicKriging.R
inst/doc/vignette_data
inst/doc/vignette_data/ig_genotypes.bed
inst/doc/vignette_data/ig_genotypes.grm.id
inst/doc/vignette_data/ig_genotypes.fam
inst/doc/vignette_data/ig_genotypes.grm.N.bin
inst/doc/vignette_data/ig_genotypes.bim
inst/doc/vignette_data/ig_pheno.txt
inst/doc/vignette_data/ig_genotypes.grm.bin
inst/doc/vignette_data/ig_gene_subset.txt.gz
inst/doc/OmicKriging.Rnw
inst/doc/OmicKriging.pdf
NAMESPACE
R
R/omic_KRIGR.R
R/input_pheno_GT.R
R/correlation_matrices.R
vignettes
vignettes/vignette_data
vignettes/vignette_data/ig_genotypes.bed
vignettes/vignette_data/ig_genotypes.grm.id
vignettes/vignette_data/ig_genotypes.fam
vignettes/vignette_data/ig_genotypes.grm.N.bin
vignettes/vignette_data/ig_genotypes.bim
vignettes/vignette_data/ig_pheno.txt
vignettes/vignette_data/ig_genotypes.grm.bin
vignettes/vignette_data/ig_gene_subset.txt.gz
vignettes/OmicKriging.Rnw
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/write_GRMBin.Rd
man/okriging.Rd
man/make_GXM.Rd
man/make_PCs_irlba.Rd
man/load_sample_data.Rd
man/krigr_cross_validation.Rd
man/read_GRMBin.Rd
man/make_PCs_svd.Rd
OmicKriging documentation built on May 19, 2017, 9:53 a.m.