kangar00 (1.3)

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, ).

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, testthat
Reverse suggests: mboost

Released over 1 year ago.