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Description

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.

Update

Code and documentation for a updated release to the Omic Kriging R package. Focused primarily on improving efficiency, improving ease of use, and reducing dependencies.

Link to latest CRAN release

Description

This package 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. More updated versions can be found here

Authors and Contributors:

  • Hae Kyung Im
  • Heather E. Wheeler
  • Keston Aquino Michaels
  • Vassily Trubetskoy.
Metadata

Version

1.4.0

License

Unknown

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