Rusilowicz, Martin James, Dickenson, Michael, Charlton, Adrian et al. (2 more authors) (2016) A batch correction method for liquid chromatography–mass spectrometry data that does not depend on quality control samples. Metabolomics. ISSN 1573-3890
Abstract
The need for reproducible and comparable results is of increasing importance in non-targeted metabolomic studies, especially when differences between experimental groups are small. Liquid chromatography– mass spectrometry spectra are often acquired batch-wise so that necessary calibrations and cleaning of the instrument can take place. However this may introduce further sources of variation, such as differences in the conditions under which the acquisition of individual batches is performed. Quality control (QC) samples are frequently employed as a means of both judging and correcting this variation. Here we show that the use of QC samples can lead to problems. The non-linearity of the response can result in substantial differences between the recorded intensities of the QCs and experimental samples, making the required adjustment difficult to predict. Furthermore, changes in the response profile between one QC interspersion and the next cannot be accounted for and QC based correction can actually exacerbate the problems by introducing artificial differences. ‘‘Background correction’’ methods utilise all experimental samples to estimate the variation over time rather than relying on the QC samples alone. We compare non-QC correction methods with standard QC correction and demonstrate their success in reducing differences between replicate samples and their potential to highlight differences between experimental groups previously hidden by instrumental variation.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Authors 2016. This content is made available by the publisher under a Creative Commons Attribution Licence. This means that a user may copy, distribute and display the resource providing that they give credit. Users must adhere to the terms of the licence. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Mathematics (York) The University of York > Faculty of Sciences (York) > Chemistry (York) The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 07 Mar 2016 12:43 |
Last Modified: | 16 Oct 2024 12:51 |
Published Version: | https://doi.org/10.1007/s11306-016-0972-2 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1007/s11306-016-0972-2 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:96122 |
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