Omics for aquatic ecotoxicology: Control of extraneous variability to enhance the analysis of environmental effects

There are multiple sources of biological and technical variation in a typical ecotoxicology study that may not be revealed by traditional endpoints but that become apparent in an omics dataset. As researchers increasingly apply omics technologies to environmental studies, it will be necessary to und...

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Published inEnvironmental toxicology and chemistry Vol. 34; no. 8; pp. 1693 - 1704
Main Authors Simmons, Denina B.D., Benskin, Jonathan P., Cosgrove, John R., Duncker, Bernard P., Ekman, Drew R., Martyniuk, Christopher J., Sherry, James P.
Format Journal Article
LanguageEnglish
Published United States Blackwell Publishing Ltd 01.08.2015
Subjects
Animals
Aquatic ecology
Control systems
Data analysis
Data processing
Design engineering
Design of experiments
Ecotoxicology
Environment effects
Environmental effects
Environmental studies
Experimental design
Female
Fishes - physiology
Genomics
Male
Metabolomics
Proteomics
Reproducibility
Research Design
Statistical methods
Statistics
Strategy
Systems toxicology
Toxicology
Transcriptomics
Variability
Metabolomics
Transcriptomics
Systems toxicology
Variability
Proteomics
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Summary:There are multiple sources of biological and technical variation in a typical ecotoxicology study that may not be revealed by traditional endpoints but that become apparent in an omics dataset. As researchers increasingly apply omics technologies to environmental studies, it will be necessary to understand and control the main source(s) of variability to facilitate meaningful interpretation of such data. For instance, can variability in omics studies be addressed by changing the approach to study design and data analysis? Are there statistical methods that can be employed to correctly interpret omics data and make use of unattributed, inherent variability? The present study presents a review of experimental design and statistical considerations applicable to the use of omics methods in systems toxicology studies. In addition to highlighting potential sources that contribute to experimental variability, this review suggests strategies with which to reduce and/or control such variability so as to improve reliability, reproducibility, and ultimately the application of omics data for systems toxicology. Environ Toxicol Chem 2015;34:1693–1704. © 2015 SETAC
Bibliography:ark:/67375/WNG-91CTX69X-Z
istex:C0C4181E31D4F81E46BB9BC17C35B3FB9678A66B
ArticleID:ETC3002
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0730-7268
1552-8618
DOI:10.1002/etc.3002