Package: kangar00
Type: Package
Title: Kernel Approaches for Nonlinear Genetic Association Regression
Version: 1.0
Date: 2017-04-26
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 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.
License: GPL-2
Collate: 'pathway.r' 'GWASdata.r' 'data.R' 'kernel.r' 'lkmt.r'
Depends: R (>= 3.1.0)
Imports: methods, KEGGgraph, biomaRt, bigmemory, sqldf, CompQuadForm,
        data.table, lattice, igraph
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
RoxygenNote: 6.0.1
Packaged: 2017-04-26 16:07:01 UTC; hofbe
Repository: CRAN
Date/Publication: 2017-04-27 11:41:53 UTC
