DRomics-shiny 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 three replicates).
After a first optional step which consists to import, check and if needed normalize/transform the data (step 1), the aim of the proposed workflow is to select monotonic and/or biphasic significantly responsive items (e.g. probes, 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).
In the available version, DRomics supports single-channel microarray data (in log2 scale), RNAseq data (in raw counts) or metabolomics data (in log scale). In order to link responses across biological levels based on a common method, DRomics also handles apical data as long as they are continuous and follow a normal distribution for each dose or concentration, with a common standard error. DRomics should not be used on other types of data.
Next, for interpretation of results in light of a biological annotation, you can use the DRomicsInterpreter-shiny application .
Links and resources
The DRomics-shiny application runs on the shiny server of the LBBE with the develoment version of the DRomics package (available on Github ).
DRomics is also an R package, available on CRAN and on this web page , where you can find also a vignette and a cheat sheet.
If you use Dromics Shiny App, you should cite:
DRomics: a turnkey tool to support the use of the dose-response framework for omics data in ecological risk assessment.
Larras F, Billoir E, Baillard V, Siberchicot A, Scholz S, Wubet T, Tarkka M, Schmitt-Jansen M and Delignette-Muller ML (2018). Environmental Science & Technology. https://doi.org/10.1021/acs.est.8b04752
You can freely find this article at: https://hal.archives-ouvertes.fr/hal-02309919
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 email@example.com .
Issues can be reported on https://github.com/aursiber/DRomics/issues .
To see what more you can do using the R package, we recommend you to consult the vignette and the cheat sheet (links to all resources here ).