Abstract
Gene-set analysis is commonly used to identify trends in gene expression when cells, tissues, organs, or organisms are subjected to conditions that differ from those within the normal physiological range. However, tools for gene-set analysis to assess liver and kidney injury responses are less common. Furthermore, most websites for gene-set analysis lack the option for users to customize their gene-set database. Here, we present the ToxPanel website, which allows users to perform gene-set analysis to assess liver and kidney injuries using activation scores based on gene-expression fold-change values. The results are graphically presented to assess constituent injury phenotypes (histopathology), with interactive result tables that identify the main contributing genes to a given signal. In addition, ToxPanel offers the flexibility to analyze any set of custom genes based on gene fold-change values. ToxPanel is publically available online at https://toxpanel.bhsai.org. ToxPanel allows users to access our previously developed liver and kidney injury gene sets, which we have shown in previous work to yield robust results that correlate with the degree of injury. Users can also test and validate their customized gene sets using the ToxPanel website.
Highlights
TOXPANEL is a web-based tool to assess liver and kidney injury from in vitro or in vivo genomic data
With the use of TG-GATE, we identified common gene responses that correlated with the severity of injury, including fibrosis, using in silico approaches
We have shown that the combination of our modular approach to identify key injury phenotype together with pathway analysis, provided in ToxPanel, can be useful when understanding the underlying molecular mechanisms in e.g., liver or kidney injury (Schyman et al, 2020a; Schyman et al, 2020b)
Summary
TOXPANEL is a web-based tool to assess liver and kidney injury from in vitro or in vivo genomic data. We previously derived 11 liver- and 8 kidney-injury modules (Te et al, 2016) from the Open Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) database (Igarashi et al, 2015), where each injury module is uniquely associated with a specific organ-injury phenotype, see Table 1. The TG-GATEs database contains gene-expression data from Sprague Dawley rats exposed to different chemicals for 4–29 days with corresponding documented and graded histopathological injury phenotypes. With the use of TG-GATE, we identified common gene responses (injury modules) that correlated with the severity of injury, including fibrosis, using in silico approaches.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
