# DRomics: Dose Response for Omics <img src="man/figures/hexsticker.png" align="right" style="float:right; height:120px;"/>

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`DRomics` is a freely available tool for dose-response (or concentration-response) characterization from omics data. It is especially dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations) rather than a great number of replicates (no need of replicates to use `DRomics`).

After a first step which consists in importing, checking and if needed normalizing/transforming the data (step 1), the aim of the proposed workflow is to select monotonic and/or biphasic significantly responsive items (e.g. probes, contigs, metabolites) (step 2), to choose the best-fit model among a predefined family of monotonic and biphasic models to describe the response of each selected item (step 3), and to derive a benchmark dose or concentration from each fitted curve (step 4). Those steps can be performed in R using `DRomics` functions, or using the shiny application named `DRomics-shiny`.

In the available version, `DRomics` supports single-channel microarray data (in log2 scale), RNAseq data (in raw counts) and other continuous omics data such as metabolomics or proteomics (in log scale). In order to link responses across biological levels based on a common method, `DRomics` also handles continuous apical data as long as they meet the use conditions of least squares regression (homoscedastic Gaussian regression).

As built in the environmental risk assessment context where omics data are more often collected on non-sequenced species or species communities, `DRomics` does not provide an annotation pipeline. The annotation of items selected by `DRomics` may be complex in this context, and must be done outside `DRomics` using databases such as KEGG or Gene Ontology. `DRomics` functions can then be used to help the interpretation of the workflow results in view of the biological annotation. It enables a multi-omics approach, with the comparison of the responses at the different levels of organization (in view of a common biological annotation). It can also be used to compare the responses at one organization level, but measured under different experimental conditions (e.g. different time points). This interpretation can be performed in R using `DRomics` functions, or using a second shiny application `DRomicsInterpreter-shiny`.

All informations about DRomics can also be found at <a href="https://lbbe.univ-lyon1.fr/fr/dromics" target="_blank">https://lbbe.univ-lyon1.fr/fr/dromics</a>.

**Keywords** : dose response modelling / benchmark dose (BMD) / environmental risk assessment / transcriptomics / proteomics / metabolomics / toxicogenomics / multi-omics


## The package 
The `limma` and `DESeq2` packages from Bioconductor must be installed for the use of `DRomics` (can take a long time):

```r
if (!requireNamespace("BiocManager", quietly = TRUE)) {
   install.packages("BiocManager")
} else {
  BiocManager::install(ask = FALSE, update = TRUE)
}

BiocManager::install(c("limma", "DESeq2"))
```

The stable version of `DRomics` can be installed from CRAN using:
```r
install.packages("DRomics")
```

The development version of `DRomics` can be installed from GitHub (`remotes` needed):
```r
if (!requireNamespace("remotes", quietly = TRUE))
   install.packages("remotes")
   
remotes::install_github("lbbe-software/DRomics")
``` 

Finally load the package in your current R session with the following R command:
```r
require("DRomics")
```


## Vignette and cheat sheet

A **vignette** is attached to the `DRomics` package.
This vignette is intended to help users to start using the `DRomics` package. It is complementary to the reference manual where you can find more details on each function of the package. The first part of this vignette (Main workflow, steps 1 to 4) could also help users of the first shiny application `DRomics-shiny`. The second part (Help for biological interpretation of `DRomics` outputs) could also help users of the second shiny application `DRomicsInterpreter-shiny`.

This vignette can be reached by:
```r
vignette("DRomics_vignette")
```

Note that, by default, the vignette is not installed when the package is installed through GitHub.
The following command (rather long to execute because of the large size of the vignette) will allow you to access the vignette of the development version of the package you installed from GitHub:
```r
remotes::install_github("lbbe-software/DRomics", build_vignettes = TRUE)
```

A **cheat sheet** that sum up the DRomics workflow is also available.
<a href="https://github.com/rstudio/cheatsheets/blob/master/DRomics.pdf"><img src="https://github.com/rstudio/cheatsheets/blob/main/pngs/DRomics.png"/></a>

## Two shiny apps 
The two shiny apps (`DRomics-shiny` and `DRomicsInterpreter-shiny`) that work with DRomics are available :

- on the LBBE shiny server at
    - https://lbbe-shiny.univ-lyon1.fr/DRomics/inst/DRomics-shiny/
    - https://lbbe-shiny.univ-lyon1.fr/DRomics/inst/DRomicsInterpreter-shiny/
- in the Biosphere cloud, if you or your lab is a partner of the IFB (Institut Français de Bioinformatique), at
    - https://biosphere.france-bioinformatique.fr/catalogue/appliance/176/ for DRomics-shiny
    - https://biosphere.france-bioinformatique.fr/catalogue/appliance/209/ for DRomicsInterpreter-shiny
- locally in your R session doing:
  - `install.packages(c("shiny", "shinyBS", "shinycssloaders", "shinyjs", "shinyWidgets", "sortable"))`
  - `shiny::runApp(system.file("DRomics-shiny", package = "DRomics"))`
  - `shiny::runApp(system.file("DRomicsInterpreter-shiny", package = "DRomics"))`

These shiny apps are runing with the development version of DRomics.



## Authors & Contacts
If you have any need that is not yet covered, any feedback on the package / Shiny app, or any training needs, feel free to email us at dromics@univ-lyon1.fr .

Issues can be reported on https://github.com/lbbe-software/DRomics/issues .

- Elise Billoir: elise.billoir@univ-lorraine.fr
- Marie-Laure Delignette-Muller: marielaure.delignettemuller@vetagro-sup.fr
- Floriane Larras: floriane.larras@kreatis.eu
- Mechthild Schmitt-Jansen: mechthild.schmitt@ufz.de
- Aurélie Siberchicot: aurelie.siberchicot@univ-lyon1.fr


## Citation
If you use Dromics, you should cite: <br />

Delignette-Muller ML, Siberchicot A, Larras F, Billoir E (2023). 
*DRomics, a workflow to exploit dose-response omics data in ecotoxicology*. 
Peer Community Journal. 
<a href="https://peercommunityjournal.org/articles/10.24072/pcjournal.325/" target="_blank">https://peercommunityjournal.org/articles/10.24072/pcjournal.325/</a>

Larras F, Billoir E, Baillard V, Siberchicot A, Scholz S, Wubet T, Tarkka M, Schmitt-Jansen M and Delignette-Muller ML (2018). 
*DRomics : a turnkey tool to support the use of the dose-response framework for omics data in ecological risk assessment*. 
Environmental Science & Technology. 
<a href="https://pubs.acs.org/doi/10.1021/acs.est.8b04752" target="_blank">https://pubs.acs.org/doi/10.1021/acs.est.8b04752</a>
You can find this article at: <a href="https://hal.science/hal-02309919" target="_blank">https://hal.science/hal-02309919</a>

You can also look at the following citation for a complete example of use: <br />
Larras F, Billoir E, Scholz S, Tarkka M, Wubet T, Delignette-Muller ML, Schmitt-Jansen M (2020). 
*A multi-omics concentration-response framework uncovers novel understanding of triclosan effects in the chlorophyte Scenedesmus vacuolatus*.
Journal of Hazardous Materials. 
<a href="https://doi.org/10.1016/j.jhazmat.2020.122727." target="_blank">https://doi.org/10.1016/j.jhazmat.2020.122727.</a>