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 |
| DOI: |
10.32614/CRAN.package.kangar00 |
| 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 |
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