Case Study
TGX – Toxicogenomics-based prediction and mechanism identification

Summary

In this case study a transcriptomics-based hazard prediction model for identification of specific molecular initiating events (MIE) will be applied based on (A) top-down and (B) bottom-up approaches.

The MIEs can include, but are not limited to: (1) Genotoxicity (p53 activation), (2) Oxidative stress (Nrf2 activation), (3) Endoplasmic Reticulum Stress (unfolded protein response), (4) Dioxin-like activity (AhR receptor activation), (5) HIF1 alpha activation and (6) Nuclear receptor activation (e.g. for endocrine disruption).

Objectives

  • Creation of prediction models based on differentially regulated genes (top-down approach);
  • Using knowledge of stress response pathways to integrate data sets for their activation or inhibition (bottom-up approach).

Risk assessment framework

This case study is associated with all 3 tiers of the selected framework and in particular the following steps:

  • Collection of support data;
  • Identification of analogues / suitability assessment and existing data;
  • Mode of Action hypothesis generation.

Use Cases Associated

This case study is associated with UC1 - Merge existing data by a common structure identifier and UC2 - Building and using a prediction model.

These two use cases are relevant for the top-down approaches:

  • Reproducing the prediction models published by Herwig et al., 2016 using data from the EU-project carcinoGENOMICs;
  • Advanced predictions using as much data as possible from the diXa data warehouse and other repositories giving free access to the data.

Databases and tools

Databases:

  • diXa (carcinoGENOMICs, Predict-IV), TG-GATEs, EU-ToxRisk (nascent), HeCaToS (nascent), ArrayExpress/GEO BioStudies.

Tools:

  • top-down: Data normalisation tools, prediction tools such as Caret;
  • bottom-up: ToxPi.

Service integration

Service integration will be needed for the omics databases; knowledge bases and data mining; processing and analysis.

Currently available services:

  • A database for curated toxicogenomic datasets
    Service type: Database / data source, Application, Visualisation tool, Software
  • Discover your variants of interest in human omics datasets
    Service type: Application, Software, Service
  • Programmatically retrieve metadata from the European Genome-phenome Archive
    Service type: Application, Service
  • Service to run Nextflow pipelines
    Service type: Workflow, Software, Service
  • Interactive computing and workflows sharing
    Service type: Workflow, Visualisation tool, Helper tool, Software, Analysis tool, Processing tool
  • Computation research made simple and reproducible
    Service type: Workflow, Database / data source, Service

Related resources

Report
Compute and data federation (Deliverable 2.5)
Evan Floden, Audald Lloret-Villas, Paolo Di Tommaso (CRG), Ola Spjuth (UU), Lucian Farcal (EwC), Tim Dudgeon (IM), Danyel Jennen (UM)
25 Jun 2019
Abstract:
This report details the work involved in the federation of compute and data resources between the OpenRiskNet e-infrastructure and external resources. The reference environment has been designed to be capable of handling the majority of requirements for users’ wishes to deploy and run services. However specific situations demand solutions where either the computation, the data or both reside outside the OpenRiskNet e-infrastructure. This deliverable is related to Tasks 2.7 (Interconnecting virtual environment with external infrastructures) and Tasks 2.8 (Federation between virtual environments). Resource intensive analyses, such as those performed in toxicogenomics, can have CPU, memory or disk requirements that cannot be assumed to be available across all deployment scenarios. Human sequencing data may have restrictions on where it can be processed and the vast quantity of this data often predicates that it is more efficient to “bring the computation to the data”. In achieving Tasks 2.7 and 2.8, we can demonstrate how the virtual environment can utilise external infrastructure including commercial cloud providers and data stores.
Related services:
EGA Beacon
EGA Metadata API

Target audience: Researchers, Data managers, Data owners, Data modellers, Bioinformaticians, Data providers
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: EwC, CRG, UM, UU, IM
Report
Webinar recording
Use Nextflow for toxicogenomics-based prediction
Evan Floden (Centre for Genomic Regulation)
3 Jun 2019

Target audience: Researchers, Developers, Data modellers, Bioinformaticians, Software developers
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: CRG
Webinar recording
Presentation
Use Nextflow for toxicogenomics-based prediction
Evan Floden (Centre for Genomic Regulation)
27 May 2019
Additional materials:
Slides

Target audience: Researchers, Students, Developers, Data modellers, Bioinformaticians
Open access: yes
Licence: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Organisations involved: CRG
Presentation