VariantScan: A Machine Learning Tool for Genetic Association Studies

Portable, scalable and highly computationally efficient tool for genetic association studies."VariantScan" provides a set of machine learning methods (Linear, Local Polynomial Regression Fitting and Generalized Additive Model with Local Polynomial Smoothing) for genetic association studies that test for disease or trait association with genetic variants (biomarkers, e.g.,genomic (genetic loci), transcriptomic (gene expressions), epigenomic (methylations), proteomic (proteins), metabolomic (metabolites)). It is particularly useful when local associations and complex nonlinear associations exist.

Version: 1.1.9
Depends: R (≥ 3.0)
Imports: stats, SNPRelate, caret, gam, ModelMetrics
Suggests: knitr, testthat, rmarkdown, ggplot2
Published: 2022-06-30
Author: Xinghu Qin ORCID iD [aut, cre, cph], Tianzi Liu [aut], Peilin Jia [aut]
Maintainer: Xinghu Qin <qin.xinghu at>
License: GPL (≥ 3)
NeedsCompilation: no
SystemRequirements: GNU make
Materials: README
CRAN checks: VariantScan results


Reference manual: VariantScan.pdf
Vignettes: Instruction for Package VariantScan


Package source: VariantScan_1.1.9.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): VariantScan_1.1.9.tgz, r-oldrel (arm64): VariantScan_1.1.9.tgz, r-release (x86_64): VariantScan_1.1.9.tgz, r-oldrel (x86_64): VariantScan_1.1.9.tgz


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