kangar00: Kernel Approaches for Nonlinear Genetic Association Regression

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.

Version: 1.0
Depends: R (≥ 3.1.0)
Imports: methods, KEGGgraph, biomaRt, bigmemory, sqldf, CompQuadForm, data.table, lattice, igraph
Suggests: knitr, rmarkdown
Published: 2017-04-27
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 at manitz.org>
License: GPL-2
NeedsCompilation: no
Citation: kangar00 citation info
CRAN checks: kangar00 results

Downloads:

Reference manual: kangar00.pdf
Vignettes: Kernel Approaches for Nonlinear Genetic Association Regression
Package source: kangar00_1.0.tar.gz
Windows binaries: r-devel: kangar00_1.0.zip, r-release: kangar00_1.0.zip, r-oldrel: kangar00_1.0.zip
OS X El Capitan binaries: r-release: not available
OS X Mavericks binaries: r-oldrel: kangar00_1.0.tgz

Reverse dependencies:

Reverse suggests: mboost

Linking:

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