SetBased Test Procedures for the Functional Analy

Authors: Jochen Kruppa Klaus Jung

Publish Date: 2016

Volume: , Issue: , Pages: 143-156

PDF Link

Abstract

The analysis of most highthroughput proteomics experiments involves the selection of differentially expressed proteins or peptides between two different sets of samples eg from two experimental groups As a result a large list of selected features is reported typically sorted by a measure for the expression fold change and a pvalue from a statistical test The biological interpretation of such a list is usually difficult since the features can typically be assigned to a large variety of biological classes To facilitate the biological interpretation setbased procedures focus on the analysis of feature subsets that all belong to the same biological class eg same cellular component biological process molecular function or pathway Setbased procedures can roughly be divided into “enrichment methods” and “global test procedures” where the first involve all features of an experiment and the second only those features of a particular set In this chapter we detail the working principle of these kind of statistical methods and describe how features can be classified into molecular subsets We illustrate the use of the methods on a data example from a proteomics Parkinson study

Keywords: