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, ).


Reference manual

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1.4 by Juliane Manitz, a year ago

Browse source code at

Authors: Juliane Manitz [aut] , Stefanie Friedrichs [aut] , Patricia Burger [aut] , Benjamin Hofner [aut] , Ngoc Thuy Ha [aut] , Saskia Freytag [ctb] , Heike Bickeboeller [ctb]

Documentation:   PDF Manual  

GPL-2 license

Imports methods, bigmemory, sqldf, biomaRt, KEGGgraph, CompQuadForm, data.table, lattice, igraph

Suggests testthat

Suggested by mboost.

See at CRAN