# LimROTS: A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust Analysis of Proteomics and Metabolomics Data
[](https://github.com/AliYoussef96/LimROTS/issues)
[](https://github.com/AliYoussef96/LimROTS/pulls)
[](https://github.com/AliYoussef96/LimROTS/actions)
<!--[](https://app.codecov.io/gh/AliYoussef96/LimROTS?branch=devel)-->
<!--[](https://www.codefactor.io/repository/github/AliYoussef96/LimROTS)-->
Differential expression analysis is a prevalent method utilised in the
examination of diverse biological data. The reproducibility-optimized test
statistic (ROTS) ([Tomi Suomi et
al.,](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005562))
has been developed with a modified t-statistic based on the data's intrinsic
characteristics and ranks features according to their statistical significance
for differential expression between two or more groups, as shown by the
f-statistic. Focusing on proteomics and metabolomics, the current ROTS
implementation cannot account for technical or biological covariates such as MS
batches or gender differences among the samples. Consequently, we developed
LimROTS, which employs a reproducibility-optimized test statistic utilizing the
limma empirical bayes ([Ritchie ME et
al.,](https://academic.oup.com/nar/article/43/7/e47/2414268)) methodology to
simulate more complex experimental designs.
## Installation instructions
### Option 1: Install from Bioconductor (recommended)
The package is available on Bioconductor as a development (devel) version. To install it, follow these steps,
``` r
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(version='devel')
BiocManager::install("LimROTS")
```
### Option 2: Install from GitHub
You can install the package directly from GitHub,
``` r
if (!requireNamespace("LimROTS", quietly = TRUE)) {
remotes::install_github("AliYoussef96/LimROTS")
}
```
or
``` r
remotes::install_github("AliYoussef96/LimROTS" , ref = "devel")
```
## Code of Conduct
Please note that the LimROTS project is released with a [Contributor Code of
Conduct](https://bioconductor.org/about/code-of-conduct/). By contributing to
this project, you agree to abide by its terms. Contributions are welcome in the
form of feedback, issues and pull requests. You can find the contributor
guidelines of the LimROTS
[here](https://github.com/AliYoussef96/LimROTS/blob/main/CONTRIBUTING.md).
## Acknowledgements
Please note that LimROTS was only made possible thanks to many other R and
rOpenGov software authors, which are cited in the vignettes describing this
package.
This package was developed using the following resources:
- [*usethis*](https://cran.r-project.org/web/packages/usethis/) to generate an
initial template.
- Continuous code testing is performed on [GitHub
actions](https://github.com/features/actions) and include R CMD check,
- Code coverage assessment is possible thanks to
[codecov](https://app.codecov.io/gh/).
- The documentation website is automatically updated thanks to
[*pkgdown*](https://cran.r-project.org/web/packages/pkgdown/).
- The documentation is formatted thanks to
[*devtools*](https://cran.r-project.org/web/packages/devtools/) and
[*roxygen2*](https://cran.r-project.org/web/packages/roxygen2/).
