Proteomic Workflows for Biomarker Identification Using Mass Spectrometry — Technical and Statistical Considerations during Initial Discovery

Proteomes

Dennis J. Orton¹ 

[1] Department of Pathology, 11th Floor Tupper Medical Building, Room 11B, Dalhousie University, Halifax, NS B3H 4R2, Canada; E-Mail:

关键词: biomarker discovery;    experimental design;    randomization;    replication;    high dimensional data;   

DOI  :  10.3390/proteomes1020109

来源: mdpi

【 摘 要 】

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.