Package: VariantScan
Version: 1.1.9
Date: 2022-06-25
Title: A Machine Learning Tool for Genetic Association Studies
Description: 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.
Authors@R: c(person("Xinghu", "Qin", role=c("aut", "cre", "cph"), email="qin.xinghu@163.com", comment=c(ORCID="0000-0003-2351-3610")),person("Tianzi", "Liu", role=c("aut"), email="liutz@big.ac.cn"),person("Peilin", "Jia", role=c("aut"), email="pjia@big.ac.cn"))
Maintainer: Xinghu Qin <qin.xinghu@163.com>
biocViews:
Depends: R (>= 3.0)
License: GPL (>= 3)
SystemRequirements: GNU make
URL: https://github.com/xinghuq/VariantScan
BugReports: https://github.com/xinghuq/VariantScan/issues
Imports: stats,SNPRelate,caret,gam,ModelMetrics
VignetteBuilder: knitr
NeedsCompilation: no
RoxygenNote: 6.1.1
Suggests: knitr,testthat,rmarkdown,ggplot2
Packaged: 2022-06-29 02:19:41 UTC; Qin_st_andrews
Author: Xinghu Qin [aut, cre, cph] (<https://orcid.org/0000-0003-2351-3610>),
  Tianzi Liu [aut],
  Peilin Jia [aut]
Repository: CRAN
Date/Publication: 2022-06-30 11:50:06 UTC
