kangar00 (1.1)

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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.

Maintainer: Juliane Manitz
Author(s): Juliane Manitz [aut], Stefanie Friedrichs [aut], Patricia Burger [aut], Benjamin Hofner [aut], Ngoc Thuy Ha [aut], Saskia Freytag [ctb], Heike Bickeboeller [ctb]

License: GPL-2

Uses: bigmemory, CompQuadForm, data.table, igraph, lattice, sqldf, knitr, rmarkdown
Reverse suggests: mboost

Released about 1 month ago.

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