dromics

Dose Response for Omics

https://github.com/lbbe-software/dromics

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
Found 8 DOI reference(s) in README
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Academic publication links
Links to: acs.org
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1 of 3 committers (33.3%) from academic institutions
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (16.5%) to scientific vocabulary

Scientific Fields

Psychology Social Sciences - 40% confidence

Last synced: 4 months ago · JSON representation

Repository

Dose Response for Omics

Basic Info

Host: GitHub
Owner: lbbe-software
Language: R
Default Branch: master
Homepage: https://lbbe-software.github.io/DRomics/
Size: 152 MB

Statistics

Stars: 7
Watchers: 2
Forks: 3
Open Issues: 0
Releases: 9

Created over 6 years ago · Last pushed 5 months ago

Metadata Files

Readme Changelog Codemeta

DRomics: Dose Response for Omics

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 https://lbbe.univ-lyon1.fr/fr/dromics.

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.

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:

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

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. https://pubs.acs.org/doi/10.1021/acs.est.8b04752 You can find this article at: https://hal.science/hal-02309919

You can also look at the following citation for a complete example of use:
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. https://doi.org/10.1016/j.jhazmat.2020.122727.

Owner

Name: lbbe-software
Login: lbbe-software
Kind: organization
Location: France

Repositories: 1
Profile: https://github.com/lbbe-software

CodeMeta (codemeta.json)

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GitHub Events

Total

Release event: 1
Watch event: 3
Push event: 32
Create event: 1

Last Year

Release event: 1
Watch event: 3
Push event: 32
Create event: 1

Committers

Last synced: over 1 year ago

All Time

Total Commits: 829
Total Committers: 3
Avg Commits per committer: 276.333
Development Distribution Score (DDS): 0.45

Past Year

Commits: 111
Committers: 2
Avg Commits per committer: 55.5
Development Distribution Score (DDS): 0.306

Top Committers

Name	Email	Commits
Aurélie Siberchicot	a**t@u**r	456
Marie-Laure DELIGNETTE-MULLER	m****e	372
BLANCHET Christophe	c**t@f**r	1

Committer Domains (Top 20 + Academic)

france-bioinformatique.fr: 1 univ-lyon1.fr: 1

Packages

Total packages: 1
Total downloads:
- cran 418 last-month
Total docker downloads: 21,613

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 11
Total maintainers: 1

cran.r-project.org: DRomics

Dose Response for Omics

Homepage: https://lbbe.univ-lyon1.fr/fr/dromics
Documentation: http://cran.r-project.org/web/packages/DRomics/DRomics.pdf
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Latest release: 2.6-2
published about 1 year ago

Versions: 11
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 418 Last month
Docker Downloads: 21,613

Rankings

Forks count: 14.9%

Stargazers count: 26.2%

Average: 29.1%

Dependent packages count: 29.8%

Dependent repos count: 35.5%

Downloads: 39.1%

Maintainers (1)

aurelie.siberchicot@univ-lyon1.fr

Last synced: 4 months ago

Dependencies

DESCRIPTION cran

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shinyWidgets * suggests
shinycssloaders * suggests
shinyjs * suggests
sortable * suggests
testthat * suggests

.github/workflows/R-CMD-check.yaml actions

actions/checkout v3 composite
r-lib/actions/check-r-package v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/pkgdown.yaml actions

JamesIves/github-pages-deploy-action 4.1.4 composite
actions/checkout v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Open Source Science

dromics

Science Score: 59.0%

Scientific Fields

Repository

Basic Info

Statistics

Metadata Files

README.md

DRomics: Dose Response for Omics

The package

Vignette and cheat sheet

Two shiny apps

Authors & Contacts

Citation

Owner

CodeMeta (codemeta.json)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Packages

cran.r-project.org: DRomics

Rankings

Maintainers (1)

Dependencies