A systematic evaluation of normalization methods in quantitative label-free proteomics

• Published in: Briefings in bioinformatics Vol. 19; no. 1; pp. 1 - 11
• Main Authors: Välikangas, Tommi, Suomi, Tomi, Elo, Laura L
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.01.2018; Oxford Publishing Limited (England)
• Subjects: Animals; data collection; Databases, Protein; Datasets; DNA chips; DNA microarrays; gene expression regulation; Humans; Instrumentation; Mass spectrometry; Mass spectroscopy; Methods; Mice; Models, Statistical; Normalizing; Peptide Mapping - methods; Peptide Mapping - standards; Proteome - analysis; Proteomics; Proteomics - methods; Proteomics - standards; Regression analysis; Reliability analysis; Reproducibility; Reproducibility of Results; variance; Variation; proteomics; normalization; intragroup variation; quantitation; reproducibility; bias; label free; differential expression; mass spectrometry; logarithmic fold change

Abstract To date, mass spectrometry (MS) data remain inherently biased as a result of reasons ranging from sample handling to differences caused by the instrumentation. Normalization is the process that aims to account for the bias and make samples more comparable. The selection of a proper normaliz...