Relative Quantification: Characterization of Bias, Variability and Fold Changes in Mass Spectrometry Data from iTRAQ-Labeled Peptides
Year: 2011
Type: article
Abstract: Shotgun proteomics via mass spectrometry (MS) is a powerful technology for biomarker discovery that has the potential to lead to noninvasive disease screening mechanisms. Successful application of MS-based proteomics technologies for biomarker discovery requires accurate expectations of bias, reproducibility, variance, and the true detectable differences in platforms chosen for analyses. Characterization of the variability inherent in MS assays is vital and should affect interpretation of measurements of observed differences in biological samples. Here we describe observed biases, variance structure, and the ability to detect known differences in spike-in data sets for which true relative abundance among defined samples were known and were subsequently measured with the iTRAQ technology on two MS platforms. Global biases were observed within these data sets. Measured variability was a function of mean abundance. Fold changes were biased toward the null and variance of a fold change was a function of protein mass and abundance. The information presented herein will be valuable for experimental design and analysis of the resulting data.
Source: Journal of Proteome Research
DOI: 10.1021/pr2001308
Institutions: Mayo Clinic, University of Minnesota
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
Funder: National Cancer Institute
Awards: G4061461591, G6433449787
OpenAlex ID: W1981601285
