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
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Abstract 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
AbstractList Abstract 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
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
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.
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.
Author Cosgrove, John R.
Benskin, Jonathan P.
Ekman, Drew R.
Sherry, James P.
Simmons, Denina B.D.
Martyniuk, Christopher J.
Duncker, Bernard P.
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Snippet There are multiple sources of biological and technical variation in a typical ecotoxicology study that may not be revealed by traditional endpoints but that...
Abstract There are multiple sources of biological and technical variation in a typical ecotoxicology study that may not be revealed by traditional endpoints...
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SubjectTerms 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
Title Omics for aquatic ecotoxicology: Control of extraneous variability to enhance the analysis of environmental effects
URI https://api.istex.fr/ark:/67375/WNG-91CTX69X-Z/fulltext.pdf
https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fetc.3002
https://www.ncbi.nlm.nih.gov/pubmed/25827364
https://www.proquest.com/docview/1700147481
https://www.proquest.com/docview/2736524041
https://search.proquest.com/docview/1705076061
https://search.proquest.com/docview/1718950543
Volume 34
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