A statistical framework for applying RNA profiling to chemical hazard detection


Use of ‘omics technologies in environmental science is expanding. However, application is mostly restricted to characterizing molecular steps leading from toxicant interaction with molecular receptors to apical endpoints in laboratory species. Use in environmental decision-making is limited, due to difficulty in elucidating mechanisms in sufficient detail to make quantitative outcome predictions in any single species or in extending predictions to aquatic communities. Here researchers from the EPA introduce a mechanism-agnostic statistical approach, supplementing mechanistic investigation by allowing probabilistic outcome prediction even when understanding of molecular pathways is limited, and facilitating extrapolation from results in laboratory test species to predictions about aquatic communities. They use concepts familiar to environmental managers, supplemented with techniques employed for clinical interpretation of ‘omics-based biomedical tests. the researchers describe the framework in step-wise fashion, beginning with single test replicates of a single RNA variant, then extending to multi-gene RNA profiling, collections of test replicates, and integration of complementary data. In order to simplify the presentation, they focus on using RNA profiling for distinguishing presence versus absence of chemical hazards, but the principles discussed can be extended to other types of ‘omics measurements, multi-class problems, and regression. They include a supplemental file demonstrating many of the concepts using the open source R statistical package.

Kostich MS. (2017) A statistical framework for applying RNA profiling to chemical hazard detection. Chemosphere 188:49-59. [Epub ahead of print]. [abstract]

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