Author: David Scott <d.scott@auckland.ac.nz> and Christine Yang Dong
Description: This package provides functions for the variance gamma
distributions. Density, distribution and quantile functions. In
addition, there are also functions for random number generation
and fitting of the variance gamma to data.

Depends: R (>= 2.3.0), HyperbolicDist (>= 0.6-2)
distributions. Density, distribution and quantile functions.
Functions for random number generation and fitting of the
variance gamma to data. Also, functions for computing moments
of the variance gamma distribution of any order about any
location. In addition, there are functions for checking the
validity of parameters and to interchange different sets of
parameterizatons for the variance gamma distribution.

Author: David Scott <d.scott@auckland.ac.nz> and
Description: Provides functions for the variance gamma
distribution. Density, distribution and quantile functions.
parameterizations for the variance gamma distribution.

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"))
Packaged: 2022-06-29 02:19:41 UTC; Qin_st_andrews
Author: Xinghu Qin [aut, cre, cph] (<https://orcid.org/0000-0003-2351-3610>),