vtrubets/OmicKriging: Poly-Omic Prediction of Complex TRaits

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.

Getting started

Package details

AuthorHae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily Trubetskoy
MaintainerHae Kyung Im <[email protected]>
LicenseGPL (>=3)
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
vtrubets/OmicKriging documentation built on Nov. 11, 2019, 2:36 p.m.