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Toward a checklist for exchange and interpretation of data from a toxicology study
Fostel, J. M., Burgoon, L., Zwickl, C., Lord, P., Corton, J. C., Bushel, P. R., Cunningham, M., Fan, L., Edwards, S. W., Hester, S., Stevens, J., Tong, W., Waters, M., Yang, C., & Tennant, R. (2007). Toward a checklist for exchange and interpretation of data from a toxicology study. Toxicological Sciences, 99(1), 26-34. https://doi.org/10.1093/toxsci/kfm090
Data from toxicology and toxicogenomics studies are valuable, and can be combined for meta-analysis using public data repositories such as Chemical Effects in Biological Systems Knowledgebase, ArrayExpress, and Gene Expression Omnibus. In order to fully utilize the data for secondary analysis, it is necessary to have a description of the study and good annotation of the accompanying data. This study annotation permits sophisticated cross-study comparison and analysis, and allows data from comparable subjects to be identified and fully understood. The Minimal Information About a Microarray Experiment Standard was proposed to permit deposition and sharing of microarray data. We propose the first step toward an analogous standard for a toxicogenomics/toxicology study, by describing a checklist of information that best practices would suggest be included with the study data. When the information in this checklist is deposited together with the study data, the checklist information helps the public explore the study data in context of time, or identify data from similarly treated subjects, and also explore/identify potential sources of experimental variability. The proposed checklist summarizes useful information to include when sharing study data for publication, deposition into a database, or electronic exchange with collaborators. It is not a description of how to carry out an experiment, but a definition of how to describe an experiment. It is anticipated that once a toxicology checklist is accepted and put into use, then toxicology databases can be configured to require and output these fields, making it straightforward to annotate data for interpretation by others.