Literature DB >> 30444611

DRomics: A Turnkey Tool to Support the Use of the Dose-Response Framework for Omics Data in Ecological Risk Assessment.

Floriane Larras1, Elise Billoir2, Vincent Baillard2, Aurélie Siberchicot3, Stefan Scholz1, Tesfaye Wubet4,5, Mika Tarkka5,6, Mechthild Schmitt-Jansen1, Marie-Laure Delignette-Muller3.   

Abstract

Omics approaches (e.g., transcriptomics, metabolomics) are promising for ecological risk assessment (ERA) since they provide mechanistic information and early warning signals. A crucial step in the analysis of omics data is the modeling of concentration-dependency which may have different trends including monotonic (e.g., linear, exponential) or biphasic (e.g., U shape, bell shape) forms. The diversity of responses raises challenges concerning detection and modeling of significant responses and effect concentration (EC) derivation. Furthermore, handling high-throughput data sets is time-consuming and requires effective and automated processing routines. Thus, we developed an open source tool (DRomics, available as an R-package and as a web-based service) which, after elimination of molecular responses (e.g., gene expressions from microarrays) with no concentration-dependency and/or high variability, identifies the best model for concentration-response curve description. Subsequently, an EC (e.g., a benchmark dose) is estimated from each curve, and curves are classified based on their model parameters. This tool is especially dedicated to manage data obtained from an experimental design favoring a great number of tested doses rather than a great number of replicates and also to handle properly monotonic and biphasic trends. The tool finally provides restitution for a table of results that can be directly used to perform ERA approaches.

Mesh:

Year:  2018        PMID: 30444611     DOI: 10.1021/acs.est.8b04752

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  6 in total

Review 1.  Metabolome response to anthropogenic contamination on microalgae: a review.

Authors:  Léa Gauthier; Juliette Tison-Rosebery; Soizic Morin; Nicolas Mazzella
Journal:  Metabolomics       Date:  2019-12-21       Impact factor: 4.290

2.  Untargeted and targeted analysis of sarin poisoning biomarkers in rat urine by liquid chromatography and tandem mass spectrometry.

Authors:  M F Vokuev; Т М Baygildiev; I V Plyushchenko; Y A Ikhalaynen; R L Ogorodnikov; I K Solontsov; А V Braun; E I Savelieva; I V Rуbalchenko; I A Rodin
Journal:  Anal Bioanal Chem       Date:  2021-09-21       Impact factor: 4.142

3.  FastBMD: an online tool for rapid benchmark dose-response analysis of transcriptomics data.

Authors:  Jessica Ewald; Othman Soufan; Jianguo Xia; Niladri Basu
Journal:  Bioinformatics       Date:  2021-05-17       Impact factor: 6.937

4.  Non-parametric synergy modeling of chemical compounds with Gaussian processes.

Authors:  Yuliya Shapovalova; Tom Heskes; Tjeerd Dijkstra
Journal:  BMC Bioinformatics       Date:  2022-01-06       Impact factor: 3.169

5.  Strengthening Causal Inference in Exposomics Research: Application of Genetic Data and Methods.

Authors:  Christy L Avery; Annie Green Howard; Anna F Ballou; Victoria L Buchanan; Jason M Collins; Carolina G Downie; Stephanie M Engel; Mariaelisa Graff; Heather M Highland; Moa P Lee; Adam G Lilly; Kun Lu; Julia E Rager; Brooke S Staley; Kari E North; Penny Gordon-Larsen
Journal:  Environ Health Perspect       Date:  2022-05-09       Impact factor: 11.035

6.  Mode of action evaluation for reduced reproduction in Daphnia pulex exposed to the insensitive munition, 1-methyl-3-nitro-1-nitroguanidine (MeNQ).

Authors:  Kurt A Gust; Guilherme R Lotufo; Natalie D Barker; Qing Ji; Lauren K May
Journal:  Ecotoxicology       Date:  2021-06-26       Impact factor: 2.823

  6 in total

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