GitHub - rauschenberger/semisup: Semi-Supervised Mixture Model (original) (raw)

Scope

Implements a parametric semi-supervised mixture model. The permutation test detects markers with main or interactive effects, without distinguishing them. Possible applications include genome-wide association studies and differential expression analyses.

Installation

The package semisup depends on R >= 3.0.0, and is available fromBioconductor:

if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install("semisup")

Alternatively, it can be installed fromGitHub. This requires the package devtools:

devtools::install_github("rauschenberger/semisup",build_vignettes=TRUE)

Please restart R before loading the package and its documentation:

library(semisup) utils::help(semisup) utils::vignette("semisup")

Reference

A Rauschenberger, RX Menezes, MA van de Wiel, NM van Schoor, and MA Jonker (2020). Semi-supervised mixture test for detecting markers associated with a quantitative trait. Manuscript in preparation. (outdated version: html pdf)