okriging: Run omic kriging on a set of correlation matrices and a given...

In OmicKriging: Poly-Omic Prediction of Complex TRaits

Description

Universal kriging formula: lambda' = ( c + X m )' iSig m' = ( x - X' iSig c )' ( X' iSig X )^-1 m' = ( t(x) - c' iSig X ) ( X' iSig X )^-1 lambda' = (c' + m' X) iSig x: #covariates x ntest X: ntrain x #cov c: ntrain x ntest

Usage

okriging(idtest, idtrain = NULL, corlist, H2vec, pheno, phenoname,
  Xcova = NULL)

Arguments

idtest	A vector of sample IDs which constitute the test set.
idtrain	A vector of sample IDs which constitute the training set.
corlist	A list of correlation matrices used in Kriging. rownames and colnames of cor should be IID list and include idtest and idtrain.
H2vec	has weights for each RM relatednes matrix
pheno	A data frame with rownames set as sample IDs and a column containing phenotype data.
phenoname	The name of the column in pheno which contains phenotype data to test.
Xcova	Data frame of covariates with rownames() set to sample IDs.

Value

A dataframe with three columns: sample ID, observed phenotype Ytest, and predicted phenotype Ypred

References

Cressie 1993 Statistics for Spatial Data p.154

OmicKriging documentation built on May 1, 2019, 9:16 p.m.