Package: OmicKriging 1.4.0
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:
OmicKriging_1.4.0.tar.gz
OmicKriging_1.4.0.zip(r-4.5)OmicKriging_1.4.0.zip(r-4.4)OmicKriging_1.4.0.zip(r-4.3)
OmicKriging_1.4.0.tgz(r-4.4-any)OmicKriging_1.4.0.tgz(r-4.3-any)
OmicKriging_1.4.0.tar.gz(r-4.5-noble)OmicKriging_1.4.0.tar.gz(r-4.4-noble)
OmicKriging_1.4.0.tgz(r-4.4-emscripten)OmicKriging_1.4.0.tgz(r-4.3-emscripten)
OmicKriging.pdf |OmicKriging.html✨
OmicKriging/json (API)
# Install 'OmicKriging' in R: |
install.packages('OmicKriging', repos = c('https://hakyimlab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/hakyimlab/omickriging/issues
Last updated 4 years agofrom:48edf855f1. Checks:ERROR: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | FAIL | Nov 12 2024 |
R-4.5-win | ERROR | Nov 12 2024 |
R-4.5-linux | ERROR | Nov 12 2024 |
R-4.4-win | ERROR | Nov 12 2024 |
R-4.4-mac | ERROR | Nov 12 2024 |
R-4.3-win | ERROR | Nov 12 2024 |
R-4.3-mac | ERROR | Nov 12 2024 |
Exports:krigr_cross_validationload_sample_datamake_GXMmake_PCs_irlbamake_PCs_svdokrigingread_GRMBinwrite_GRMBin
Dependencies:bitopscaToolscodetoolsdoParallelforeachgplotsgtoolsirlbaiteratorsKernSmoothlatticeMatrixROCR
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Multithreaded cross validation routine for Omic Kriging. | krigr_cross_validation |
Loads sample phenotype and covariate data into data frame. | load_sample_data |
Compute gene expression correlation matrix. | make_GXM |
Run Principal Component Analysis (PCA) using the irlba package. | make_PCs_irlba |
Run Principal Component Analysis (PCA) using base R svd() function. | make_PCs_svd |
Run omic kriging on a set of correlation matrices and a given phenotype. | okriging |
Read the GRM binary file. | read_GRMBin |
Write GRM binary files. | write_GRMBin |