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Quality assurance and quality control reporting in untargeted metabolic phenotyping: mQACC recommendations for analytical quality management
by
Gika, Helen
, Beger, Richard D
, Bearden, Dan
, Wilson, Ian D
, Witting, Michael
, Yu, Li-Rong
, Theodoridis, Georgios
, Dunn, Warwick B
, Goodacre, Royston
, Kirwan, Jennifer A
in
Magnetic resonance spectroscopy
/ Mass spectroscopy
/ Metabolism
/ Metabolomics
/ NMR
/ Nuclear magnetic resonance
/ Phenotyping
/ Quality assurance
/ Quality control
2022
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Quality assurance and quality control reporting in untargeted metabolic phenotyping: mQACC recommendations for analytical quality management
by
Gika, Helen
, Beger, Richard D
, Bearden, Dan
, Wilson, Ian D
, Witting, Michael
, Yu, Li-Rong
, Theodoridis, Georgios
, Dunn, Warwick B
, Goodacre, Royston
, Kirwan, Jennifer A
in
Magnetic resonance spectroscopy
/ Mass spectroscopy
/ Metabolism
/ Metabolomics
/ NMR
/ Nuclear magnetic resonance
/ Phenotyping
/ Quality assurance
/ Quality control
2022
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Quality assurance and quality control reporting in untargeted metabolic phenotyping: mQACC recommendations for analytical quality management
by
Gika, Helen
, Beger, Richard D
, Bearden, Dan
, Wilson, Ian D
, Witting, Michael
, Yu, Li-Rong
, Theodoridis, Georgios
, Dunn, Warwick B
, Goodacre, Royston
, Kirwan, Jennifer A
in
Magnetic resonance spectroscopy
/ Mass spectroscopy
/ Metabolism
/ Metabolomics
/ NMR
/ Nuclear magnetic resonance
/ Phenotyping
/ Quality assurance
/ Quality control
2022
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Quality assurance and quality control reporting in untargeted metabolic phenotyping: mQACC recommendations for analytical quality management
Journal Article
Quality assurance and quality control reporting in untargeted metabolic phenotyping: mQACC recommendations for analytical quality management
2022
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Overview
BackgroundDemonstrating that the data produced in metabolic phenotyping investigations (metabolomics/metabonomics) is of good quality is increasingly seen as a key factor in gaining acceptance for the results of such studies. The use of established quality control (QC) protocols, including appropriate QC samples, is an important and evolving aspect of this process. However, inadequate or incorrect reporting of the QA/QC procedures followed in the study may lead to misinterpretation or overemphasis of the findings and prevent future metanalysis of the body of work.ObjectiveThe aim of this guidance is to provide researchers with a framework that encourages them to describe quality assessment and quality control procedures and outcomes in mass spectrometry and nuclear magnetic resonance spectroscopy-based methods in untargeted metabolomics, with a focus on reporting on QC samples in sufficient detail for them to be understood, trusted and replicated. There is no intent to be proscriptive with regard to analytical best practices; rather, guidance for reporting QA/QC procedures is suggested. A template that can be completed as studies progress to ensure that relevant data is collected, and further documents, are provided as on-line resources.Key reporting practicesMultiple topics should be considered when reporting QA/QC protocols and outcomes for metabolic phenotyping data. Coverage should include the role(s), sources, types, preparation and uses of the QC materials and samples generally employed in the generation of metabolomic data. Details such as sample matrices and sample preparation, the use of test mixtures and system suitability tests, blanks and technique-specific factors are considered and methods for reporting are discussed, including the importance of reporting the acceptance criteria for the QCs. To this end, the reporting of the QC samples and results are considered at two levels of detail: “minimal” and “best reporting practice” levels.
Publisher
Springer Nature B.V
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