NDLI: Controlling the quality of metabolomics data: new strategies to get the best out of the QC sample

Content Provider	Springer Nature Link
Author	Godzien, Joanna Alonso Herranz, Vanesa Barbas, Coral Armitage, Emily Grace
Copyright Year	2014
Abstract	The type and use of quality control (QC) samples is a ‘hot topic’ in metabolomics. QCs are not novel in analytical chemistry; however since the evolution of using QCs to control the quality of data in large scale metabolomics studies (first described in 2011), the need for detailed knowledge of how to use QCs and the effects they can have on data treatment is growing. A controlled experiment has been designed to illustrate the most advantageous uses of QCs in metabolomics experiments. For this, samples were formed from a pool of plasma whereby different metabolites were spiked into two groups in order to simulate biological biomarkers. Three different QCs were compared: QCs pooled from all samples, QCs pooled from each experimental group of samples separately and QCs provided by an external source (QC surrogate). On the experimentation of different data treatment strategies, it was revealed that QCs collected separately for groups offers the closest matrix to the samples and improves the statistical outcome, especially for biomarkers unique to one group. A novel quality assurance plus procedure has also been proposed that builds on previously published methods and has the ability to improve statistical results for QC pool. For this dataset, the best option to work with QC surrogate was to filter data based only on group presence. Finally, a novel use of recursive analysis is portrayed that allows the improvement of statistical analyses with respect to the ratio between true and false positives.
Starting Page	518
Ending Page	528
Page Count	11
File Format	PDF
ISSN	15733882
Journal	Metabolomics
Volume Number	11
Issue Number	3
e-ISSN	15733890
Language	English
Publisher	Springer US
Publisher Date	2014-07-27
Publisher Institution	Metabolomics Society
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Quality control samples Quality assurance procedure False positives Recursive analysis In silico QC surrogate Biochemistry Molecular Medicine Cell Biology Developmental Biology Biomedicine general
Content Type	Text
Resource Type	Article
Subject	Endocrinology, Diabetes and Metabolism Clinical Biochemistry Biochemistry

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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