jmanitz/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>).
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Package details |
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| 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@manitz.org> |
| License | GPL-2 |
| Version | 1.4.1 |
| URL | https://kangar00.manitz.org/ |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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