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Normalization in MALDI-TOF imaging datasets of proteins: Practical considerations.
Anal. Bioanal. Chem. 401, 167-181 (2011)
Normalization is critically important for the proper interpretation of matrix-assisted laser desorption/ionization (MALDI) imaging datasets. The effects of the commonly used normalization techniques based on total ion count (TIC) or vector norm normalization are significant, and they are frequently beneficial. In certain cases, however, these normalization algorithms may produce misleading results and possibly lead to wrong conclusions, e.g. regarding to potential biomarker distributions. This is typical for tissues in which signals of prominent abundance are present in confined areas, such as insulin in the pancreas or β-amyloid peptides in the brain. In this work, we investigated whether normalization can be improved if dominant signals are excluded from the calculation. Because manual interaction with the data (e.g., defining the abundant signals) is not desired for routine analysis, we investigated two alternatives: normalization on the spectra noise level or on the median of signal intensities in the spectrum. Normalization on the median and the noise level was found to be significantly more robust against artifact generation compared to normalization on the TIC. Therefore, we propose to include these normalization methods in the standard "toolbox" of MALDI imaging for reliable results under conditions of automation.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Bioanalytical methods; Biological samples; Genomics/proteomics; MALDI imaging; Normalization; Data processing
Language
english
Publication Year
2011
HGF-reported in Year
2011
ISSN (print) / ISBN
1618-2642
e-ISSN
1618-2650
Quellenangaben
Volume: 401,
Issue: 1,
Pages: 167-181
Publisher
Springer
Publishing Place
Heidelberg
Reviewing status
Peer reviewed
POF-Topic(s)
30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
30205 - Bioengineering and Digital Health
30205 - Bioengineering and Digital Health
Research field(s)
Enabling and Novel Technologies
PSP Element(s)
G-500300-001
G-500390-001
G-500390-001
PubMed ID
21479971
Scopus ID
79960556909
Erfassungsdatum
2011-09-15