title: Statistical methods for quantitative mass spectrometry proteomic experiments with labeling.
abstract: Mass Spectrometry utilizing labeling allows multiple specimens to be subjected to mass spectrometry simultaneously. As a result, between-experiment variability is reduced. Here we describe use of fundamental concepts of statistical experimental design in the labeling framework in order to minimize variability and avoid biases. We demonstrate how to export data in the format that is most efficient for statistical analysis. We demonstrate how to assess the need for normalization, perform normalization, and check whether it worked. We describe how to build a model explaining the observed values and test for differential protein abundance along with descriptive statistics and measures of reliability of the findings. Concepts are illustrated through the use of three case studies utilizing the iTRAQ 4-plex labeling protocol.
authors.affiliation: Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. oberg.ann@mayo.edu
authors.forename: Ann L
authors.initials: AL
authors.lastname: Oberg
authors.forename: Douglas W
authors.initials: DW
authors.lastname: Mahoney
mesh_terms: D001699:Biometry / Q000379:methods*; D006801:Humans; D007553:Isotope Labeling; D008297:Male; D013058:Mass Spectrometry / Q000706:statistics & numerical data*; D011471:Prostatic Neoplasms / Q000378:metabolism; D011506:Proteins / Q000032:analysis / Q000737:chemistry; D040901:Proteomics / Q000706:statistics & numerical data*; D015203:Reproducibility of Results
chemical_list: D011506:Proteins