kangar00: Kernel Approaches for Nonlinear Genetic Association Regression

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>).

Version: 1.4.1
Depends: R (≥ 3.5.0)
Imports: methods, bigmemory, sqldf, biomaRt, KEGGgraph, CompQuadForm, data.table, lattice, igraph
Suggests: testthat
Published: 2022-12-06
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


Reference manual: kangar00.pdf


Package source: kangar00_1.4.1.tar.gz
Windows binaries: r-prerel: kangar00_1.4.1.zip, r-release: kangar00_1.4.1.zip, r-oldrel: kangar00_1.4.1.zip
macOS binaries: r-prerel (arm64): kangar00_1.4.1.tgz, r-release (arm64): kangar00_1.4.1.tgz, r-oldrel (arm64): kangar00_1.4.1.tgz, r-prerel (x86_64): kangar00_1.4.1.tgz, r-release (x86_64): kangar00_1.4.1.tgz
Old sources: kangar00 archive

Reverse dependencies:

Reverse suggests: mboost


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