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Sample Handling and Automation: Outlier

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Encyclopedia of Lipidomics

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Synonyms

Anomaly; Exception; Irregularity

Definition

An outlier is an extreme sample distant from the majority of other samples (Grubbs 1969). In lipidomics, this represents a sample where one or more lipid measures are distant from the other samples such that the lipid profile as a whole can be considered an outlier.

Introduction

An outlier pattern for a given sample could be a result of either the inherent characteristics of the sample (representing biological diversity) or technical error in the measurements. In lipidomics studies, such technical variation may arise from incorrect handling of the sample (including transportation, centrifugation, extraction procedures, addition of internal standards, mass spectrometry analysis, and many other processes).

Such data quality issues must be addressed prior to performing any advanced statistical analysis. A small proportion of unchecked technical outliers in a given dataset have the potential to bias the statistical parameter estimation,...

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References

  • Grubbs FE. Procedures for detecting outlying observations in samples. Technometrics. 1969;11(1):1–21.

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  • Hodge VJ, Austin J. A survey of outlier detection methodologies. Artif Intell Rev. 2004;22:85–126.

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  • Rousseeuw PJ, Leroy AM. Robust regression and outlier detection. New York: Wiley; 1996.

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  • Zimek A, Schubert E, Kriegel H-P. A survey on unsupervised outlier detection in high-dimensional numerical data. Stat Anal Data min. 2012;5(5):363–87.

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Author information

Authors and Affiliations

  1. Baker IDI Heart and Diabetes Institute, 75 Commercial Road, Melbourne, 3004, VIC, Australia

    Piyushkumar A Mundra, Kevin Huynh & Peter J. Meikle

  2. School of Medicine, Monash University, Melbourne, VIC, Australia

    Kevin Huynh & Peter J. Meikle

  3. Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, VIC, Australia

    Peter J. Meikle

Authors
  1. Piyushkumar A Mundra
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  2. Kevin Huynh
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  3. Peter J. Meikle
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Corresponding author

Correspondence to Peter J. Meikle .

Editor information

Editors and Affiliations

  1. Yong Loo Lin School of Medicine Centre for Life Sciences, Singapore, Singapore

    Markus R. Wenk

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© 2015 Springer Science+Business Media Dordrecht

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Mundra, P.A., Huynh, K., Meikle, P.J. (2015). Sample Handling and Automation: Outlier. In: Wenk, M. (eds) Encyclopedia of Lipidomics. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7864-1_56-1

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  • DOI: https://doi.org/10.1007/978-94-007-7864-1_56-1

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  • Publisher Name: Springer, Dordrecht

  • Online ISBN: 978-94-007-7864-1

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