ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets

Author:

Nair Sisira Kadambat1,Eeles Christopher1,Ho Chantal1,Beri Gangesh1,Yoo Esther1,Tkachuk Denis1,Tang Amy1,Nijrabi Parwaiz12,Smirnov Petr12ORCID,Seo Heewon1,Jennen Danyel3,Haibe-Kains Benjamin12456ORCID

Affiliation:

1. Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 0A3, Canada

2. Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada

3. Department of Toxicogenomics, GROW School of Oncology and Development Biology, Maastricht University, Maastricht, The Netherlands

4. Department of Computer Science, University of Toronto, Toronto, ON M5T 3A1, Canada

5. Ontario Institute for Cancer Research, Toronto, ON M5G 1L7, Canada

6. Vector Institute for Artificial Intelligence, Toronto, ON M5G 1L7, Canada

Abstract

Abstract In the past few decades, major initiatives have been launched around the world to address chemical safety testing. These efforts aim to innovate and improve the efficacy of existing methods with the long-term goal of developing new risk assessment paradigms. The transcriptomic and toxicological profiling of mammalian cells has resulted in the creation of multiple toxicogenomic datasets and corresponding tools for analysis. To enable easy access and analysis of these valuable toxicogenomic data, we have developed ToxicoDB (toxicodb.ca), a free and open cloud-based platform integrating data from large in vitro toxicogenomic studies, including gene expression profiles of primary human and rat hepatocytes treated with 231 potential toxicants. To efficiently mine these complex toxicogenomic data, ToxicoDB provides users with harmonized chemical annotations, time- and dose-dependent plots of compounds across datasets, as well as the toxicity-related pathway analysis. The data in ToxicoDB have been generated using our open-source R package, ToxicoGx (github.com/bhklab/ToxicoGx). Altogether, ToxicoDB provides a streamlined process for mining highly organized, curated, and accessible toxicogenomic data that can be ultimately applied to preclinical toxicity studies and further our understanding of adverse outcomes.

Publisher

Oxford University Press (OUP)

Subject

Genetics

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