https://github.com/bioconductor-source/semisup

https://github.com/bioconductor-source/semisup

Repository

README.Rmd

---
output: github_document
---



```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
```

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## 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](https://cran.r-project.org/), and is available from [Bioconductor](http://bioconductor.org/packages/semisup/):
```{r eval=FALSE}
if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("semisup")
```

Alternatively, it can be installed from [GitHub](https://github.com/rauschenberger/semisup). This requires the package [devtools](https://CRAN.R-project.org/package=devtools):
```{r eval=FALSE}
devtools::install_github("rauschenberger/semisup",build_vignettes=TRUE)
```

Please restart R before loading the package and its documentation:
```{r eval=FALSE}
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 (outdated version: [html](https://arxiv.org/abs/1805.09175) [pdf](https://arxiv.org/pdf/1805.09175))

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