Package: kangar00
Type: Package
Title: Kernel Approaches for Nonlinear Genetic Association Regression
Version: 1.3
Date: 2019-02-02
Author: Juliane Manitz [aut], Stefanie Friedrichs [aut], Patricia Burger [aut],
    Benjamin Hofner [aut], Ngoc Thuy Ha [aut], Saskia Freytag [ctb],
    Heike Bickeboeller [ctb]
Maintainer: Juliane Manitz <r@manitz.org>
Description: Methods to extract information on pathways, genes and various single-nucleotid polymorphisms (SNPs) from online databases. It provides functions for data preparation and evaluation of genetic influence on a binary outcome using the logistic kernel machine test (LKMT). Three different kernel functions are offered to analyze genotype information in this variance component test: A linear kernel, a size-adjusted kernel and a network-based kernel (Friedrichs et al., 2017, <doi:10.1155/2017/6742763>).
License: GPL-2
Collate: 'pathway.r' 'GWASdata.r' 'data.R' 'kernel.r' 'lkmt.r'
Depends: R (>= 3.1.0)
Imports: methods, biomaRt, bigmemory, sqldf, CompQuadForm, data.table,
        lattice, igraph
LazyData: true
Suggests: testthat
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2019-02-09 20:51:06 UTC; jmanitz
Repository: CRAN
Date/Publication: 2019-02-10 03:43:16 UTC
