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.

Package details

AuthorHae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily Trubetskoy
Date of publication2016-03-08 00:12:43
MaintainerHae Kyung Im <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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OmicKriging documentation built on May 29, 2017, 12:04 p.m.