Skip to main content

Sample Handling and Automation: Drift

  • Living reference work entry
  • First Online:
Encyclopedia of Lipidomics
  • 282 Accesses

Definition

Drift of an analytical method is a gradual, directional change of the method’s performance as a function of time. In other words, we observe drift in a given method, when in a series of measurements of identical samples a gradual increase or decrease of performance (for example, its precision, accuracy, or simply measured values) occurs over time.

Drift can be caused by changes in chromatographic performance (e.g., column aging), contamination or dirtying of the ion source, changes in quality of chemicals during the analysis, sample decomposition during the time it awaits its measurement, background intensity changes, and instrumental drift or offset (Kamleh et al. 2012).

There are several ways of reducing drift or correcting for it. It can be reduced by analyzing samples in small batches batch effect only and thereby minimizing the time between the acquisition of the first and the last sample (Zelena et al. 2009). Furthermore, equilibration of the analytical system until...

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

References

  • Dunn WB, Wilson ID, Nicholls AW, Broadhurst D. The importance of experimental design and QC samples in large-scale and MS-driven untargeted metabolomic studies of humans. Bioanalysis. 2012;4(18):2249–64.

    Article  CAS  PubMed  Google Scholar 

  • Kamleh MA, Ebbels TMD, Spagou K, Masson P, Want EJ. Optimizing the use of quality control samples for signal drift correction in large-scale urine metabolic profiling studies. Anal Chem. 2012;84(6):2670–7.

    Article  CAS  PubMed  Google Scholar 

  • van der Kloet FM, Bobeldijk I, Verheij ER, Jellema RH. Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping. J Proteome Res. 2009;8(11):5132–41.

    Article  PubMed  Google Scholar 

  • Wang S-Y, Kuo C-H, Tseng YJ. Batch Normalizer: a fast total abundance regression calibration method to simultaneously adjust batch and injection order effects in liquid chromatography/time-of-flight mass spectrometry-based metabolomics data and comparison with current calibration methods. Anal Chem. 2013;85(2):1037–46.

    Article  CAS  PubMed  Google Scholar 

  • Zelena E, Dunn WB, Broadhurst D, Francis-McIntyre S, Carroll KM, Begley P, et al. Development of a robust and repeatable UPLC-MS method for the long-term metabolomic study of human serum. Anal Chem. 2009;81(4):1357–64.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christian Klose .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media Dordrecht

About this entry

Cite this entry

Klose, C. (2015). Sample Handling and Automation: Drift. In: Wenk, M. (eds) Encyclopedia of Lipidomics. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7864-1_55-1

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-7864-1_55-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Online ISBN: 978-94-007-7864-1

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

Publish with us

Policies and ethics