- Abstract:
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We demonstrate how different normalization techniques in GC‐MS analysis impart unique properties to the data, influencing any biological inference. Using simulations, and empirical data, we compare the most commonly used techniques (Total Sum Normalization ‘TSN’; Median Normalization ‘MN’; Probabilistic Quotient Normalization ‘PQN’; Internal Standard Normalization ‘ISN’; External Standard Normalization ‘ESN’; and a compositional data approach ‘CODA’). When differences between biological class...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted Manuscript
- Files:
-
-
(pdf, 3.9mb)
-
- Publisher copy:
- 10.1002/bies.201700210
-
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- Publisher:
- Wiley Publisher's website
- Journal:
- BioEssays Journal website
- Volume:
- 40
- Issue:
- 6
- Pages:
- Article: 1700210
- Publication date:
- 2018-04-30
- Acceptance date:
- 2018-03-07
- DOI:
- EISSN:
-
1521-1878
- ISSN:
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0265-9247
- Pubs id:
-
pubs:828295
- URN:
-
uri:8d6a410f-1574-42bd-8755-d1253854532b
- UUID:
-
uuid:8d6a410f-1574-42bd-8755-d1253854532b
- Local pid:
- pubs:828295
- Copyright holder:
- Wiley Periodicals, Inc.
- Copyright date:
- 2018
- Notes:
-
Copyright © 2018 Wiley Periodicals, Inc. This is the accepted manuscript version of the article. The final version is available online from Wiley at: https://doi.org/10.1002/bies.201700210
Journal article
Normalizing gas‐chromatography–mass spectrometry data: method choice can alter biological inference
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