Important Issues in Planning a Proteomics Experiment: Statistical Considerations of Quantitative Proteomic Data

Methods Mol Biol. 2021;2228:1-20. doi: 10.1007/978-1-0716-1024-4_1.

Abstract

Mass spectrometry is frequently used in quantitative proteomics to detect differentially regulated proteins. A very important but unfortunately oftentimes neglected part in detecting differential proteins is the statistical analysis. Data from proteomics experiments are usually high-dimensional and hence require profound statistical methods. It is especially important to already correctly design a proteomic experiment before it is conducted in the laboratory. Only this can ensure that the statistical analysis is capable of detecting truly differential proteins afterward. This chapter thus covers aspects of both statistical planning as well as the actual analysis of quantitative proteomic experiments.

Keywords: Data preprocessing; Experimental design; Fold change; Multiple testing; Normalization; Sample size calculation; Statistical hypothesis test; Volcano plot.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Data Interpretation, Statistical
  • Humans
  • Mass Spectrometry / statistics & numerical data*
  • Models, Statistical
  • Proteins / analysis*
  • Proteome*
  • Proteomics / statistics & numerical data*
  • Research Design / statistics & numerical data*

Substances

  • Proteins
  • Proteome