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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).

Version: 1.4.2
Depends: R (≥ 3.5.0)
Imports: methods, bigmemory, sqldf, CompQuadForm, data.table, lattice, igraph
Suggests: biomaRt, KEGGgraph, testthat
Published: 2024-05-09
Author: Juliane Manitz [aut, cre], Benjamin Hofner [aut], Stefanie Friedrichs [aut], Patricia Burger [aut], Ngoc Thuy Ha [aut], Saskia Freytag [ctb], Heike Bickeboeller [ctb]
Maintainer: Juliane Manitz <r at manitz.org>
BugReports: https://github.com/jmanitz/kangar00/issues
License: GPL-2
URL: https://kangar00.manitz.org/
NeedsCompilation: no
Citation: kangar00 citation info
CRAN checks: kangar00 results

Documentation:

Reference manual: kangar00.pdf

Downloads:

Package source: kangar00_1.4.2.tar.gz
Windows binaries: r-devel: kangar00_1.4.2.zip, r-release: kangar00_1.4.2.zip, r-oldrel: kangar00_1.4.2.zip
macOS binaries: r-release (arm64): kangar00_1.4.2.tgz, r-oldrel (arm64): kangar00_1.4.2.tgz, r-release (x86_64): kangar00_1.4.2.tgz, r-oldrel (x86_64): kangar00_1.4.2.tgz
Old sources: kangar00 archive

Reverse dependencies:

Reverse suggests: mboost

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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