Package: OmicKriging 1.4.0

Hae Kyung Im

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.

Authors:Hae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily Trubetskoy

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OmicKriging.pdf |OmicKriging.html✨
OmicKriging/json (API)

Peer review:

Bug tracker:https://github.com/hakyimlab/omickriging/issues

On CRAN:

8 exports 2 stars 1.46 score 13 dependencies 1 mentions 47 scripts 175 downloads

Last updated 4 years agofrom:48edf855f1. Checks:ERROR: 7. Indexed: yes.

Exports:krigr_cross_validationload_sample_datamake_GXMmake_PCs_irlbamake_PCs_svdokrigingread_GRMBinwrite_GRMBin

Dependencies:bitopscaToolscodetoolsdoParallelforeachgplotsgtoolsirlbaiteratorsKernSmoothlatticeMatrixROCR