Package: kangar00
Type: Package
Title: Kernel Approaches for Nonlinear Genetic Association Regression
Version: 1.4.2
Date: 2024-05-09
Authors@R: c(
    person("Juliane", "Manitz", role =  c("aut","cre"), email = "r@manitz.org"), 
    person("Benjamin", "Hofner", role= "aut"), 
    person("Stefanie", "Friedrichs", role = "aut"),  
    person("Patricia", "Burger", role = "aut"),  
    person("Ngoc Thuy", "Ha", role="aut"), 
    person("Saskia", "Freytag", role="ctb"),
    person("Heike", "Bickeboeller", role="ctb"))
URL: https://kangar00.manitz.org/
BugReports: https://github.com/jmanitz/kangar00/issues
Description: 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).
License: GPL-2
Encoding: UTF-8
Collate: 'pathway.r' 'GWASdata.r' 'data.R' 'get_network_matrix.r'
        'kernel.r' 'lkmt.r'
Depends: R (>= 3.5.0)
Imports: methods, bigmemory, sqldf, CompQuadForm, data.table, lattice,
        igraph
LazyData: true
Suggests: biomaRt, KEGGgraph, testthat
NeedsCompilation: no
RoxygenNote: 7.3.1
Config/pak/sysreqs: libglpk-dev libxml2-dev
Repository: https://jmanitz.r-universe.dev
Date/Publication: 2024-09-09 16:43:42 UTC
RemoteUrl: https://github.com/jmanitz/kangar00
RemoteRef: HEAD
RemoteSha: a91c39f643e9f8c9d073478f3694efe42f65b357
Packaged: 2026-10-01 09:41:13 UTC; root
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@manitz.org>