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  [aut,
cre, cph],
Tianzi Liu [aut],
Peilin Jia [aut] |
| Maintainer: |
Xinghu Qin <qin.xinghu at 163.com> |
| BugReports: |
https://github.com/xinghuq/VariantScan/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/xinghuq/VariantScan |
| NeedsCompilation: |
no |
| SystemRequirements: |
GNU make |
| Materials: |
README |
| CRAN checks: |
VariantScan results |
Documentation:
Downloads:
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