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SYSTEMATIC OMICS ANALYSIS REVIEW TOOL TO SUPPORT RISK ASSESSMENT

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Date
2013-04-23
Author
McConnell, Emma R.
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Abstract
Environmental health risk assessors are challenged to understand and incorporate new data streams as the field of toxicology continues to adopt new molecular and systems biology technologies. Systematic screening reviews can help risk assessors determine which studies to consider for inclusion in a human health assessment. A tool for systematic reviews should be standardized and transparent in order to consistently determine which studies meet minimum quality criteria prior to performing in-depth analyses of the data. The Systematic Omics Analysis Review (SOAR) tool is a spreadsheet of 35 objective questions developed by domain experts, focused on transcriptomic microarray studies, and including four main topics: test system, test substance, experimental design, and microarray data. The tool will be used as a guide to identify studies that meet basic published quality criteria, such as those defined by the Minimum Information About a Microarray Experiment (MIAME) standard and the Toxicological data Reliability assessment Tool (ToxR Tool). Seven scientists were recruited to test the tool by using it to rate 19 published manuscripts that study chemical exposures with microarrays. Using their feedback, questions were weighted based on importance of the information and a suitability cutoff was set for each of the four topic sections. The final validation resulted in 100% agreement between the users on four separate manuscripts, showing that the SOAR tool may be used to facilitate the standardized and transparent screening of microarray literature for environmental human health risk assessment.
Type
Master's project
Department
Nicholas School of the Environment and Earth Sciences
Permalink
https://hdl.handle.net/10161/6699
Citation
McConnell, Emma R. (2013). SYSTEMATIC OMICS ANALYSIS REVIEW TOOL TO SUPPORT RISK ASSESSMENT. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/6699.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

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