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epistasis
View on CRAN: Click
here
Download and install epistasis package within the R console
Install from CRAN:
install.packages("epistasis")
Install from Github:
library("remotes")
install_github("cran/epistasis") Install by package version:
library("remotes")
install_version("epistasis", "0.0.1-1") Attach the package and use:
library("epistasis")
Maintained by
Pariya Behrouzi
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-11-07
Latest Update:
Description:
An efficient multi-core package to reconstruct an underlying network of
genomic signatures of high-dimensional epistatic selection from
partially observed genotype data. The phenotype that we consider is viability.
The network captures the conditional dependent short- and long-range linkage
disequilibrium structure of genomes and thus reveals aberrant marker-marker
associations that are due to epistatic selection. We target on high-dimensional
genotype data where number of variables (markers) is larger than number of
sample sizes (p >> n). The computations is memory-optimized using the sparse
matrix output.
How to cite:
Pariya Behrouzi (2016). epistasis: Detecting Epistatic Selection with Partially Observed Genotype
Data. R package version 0.0.1-1, https://cran.r-project.org/web/packages/epistasis. Accessed 07 Oct. 2026.
Previous versions and publish date:
Other packages that cited epistasis R package
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Other R packages that epistasis depends,
imports, suggests or enhances
Functions, R codes and Examples using
the epistasis R package
Some associated functions: B73Ki11 . CviCol . R.approx . R.gibbs . cutoffs . episelect . episim . epistasis-internal . epistasis-package . epistasis . lower.upper . plot.epi . plot.episelect . plot.episim . print.epi . print.episim .
Some associated R codes: Gibbs_method.R . R.approx.R . R.gibbs.R . approx_method.R . calculate_EM_Gibbs.R . calculate_EM_approx.R . cond_N.R . cutoffs.R . element_S.R . episelect.R . episim.R . epistasis.R . initialize.R . lower.upper.R . model.selection.R . rmvt.R . Full epistasis package functions and examples
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