Epistatic and penetrance models for two-locus genetic
interactions
Raymond Walters, Charles Laurin, Gitta Lubke
The 'epi2loc' package provides a set of utilities for using common models of epistasis. Interactions between two biallelic loci (e.g. SNPs) can easily be represented using GLM regression parameters, penetrance models, or variance components. Functions are included for conversion among these common interaction models, as well as data generation, power analysis, and effect size measures.

Process Nanopore EPI2ME Output for Use in R
c(person("Maggie", "Weinroth", role = c("aut")),
person(c('Quentin', 'D.'), 'Read', email = 'quentin.read@usda.gov', role = c('aut', 'cre')))
The functions in this package take WIMP and ARMA data files generated by Oxford Nanopore EPI2ME workflows,
read them, clean them, and prepare them for downstream analysis.
This package was written by United States federal government employees in their official capacity. Therefore, it is not protected by copyright and is in the public domain.
data.table, taxonomizr, phyloseq, Biobase, metagenomeSeq
rmarkdown, knitr, reshape2, testthat (>= 3.0.0)
Maggie Weinroth [aut],
Quentin D. Read [aut, cre]

R (>= 2.6.2), foreign, survival, MASS, nnet
Package for data exploration and result presentation.
Full 'epicalc' package with data management functions is available
at the author's repository.

Package for data exploration and result presentation. Full 'epicalc' package with data management functions is available at '<http://medipe.psu.ac.th/epicalc>'.
2018-05-10 17:12:26 UTC; Virasakdi's Surface

Package for data exploration and result presentation. Full 'epicalc' package with data management functions is available at '<https://medipe.psu.ac.th/epicalc/>'.

c(person("Lotfi", "Slim", email = "lotfi.slim@mines-paristech.fr", role = c("aut", "cre")),
person("Clément", "Chatelain", email = "clement.chatelain@sanofi.com", role = "ctb"),
person("Chloé-Agathe", "Azencott", email = "chloe-agathe.azencott@mines-paristech.fr", role ="ctb"),
person("Jean-Philippe", "Vert", email = "jpvert@google.com", role ="ctb"))
Functions to perform robust epistasis detection in genome-wide
association studies, as described in Slim et al. (2018) <doi:10.1101/442749>.
The implemented methods identify pairwise interactions between a particular
target variant and the rest of the genotype, using a propensity score
approach. The propensity score models the linkage disequilibrium between the
target and the rest of the genotype. All methods are penalized regression
approaches, which differently incorporate the propensity score to only
recover the synergistic effects between the target and the genotype.
foreach, iterators, precrec, parallel, doParallel, bigmemory,
biglasso, testthat, knitr, rmarkdown, kableExtra
Lotfi Slim [aut, cre],
Clément Chatelain [ctb],
Chloé-Agathe Azencott [ctb],
Jean-Philippe Vert [ctb]