Analyzing the Structure of Pathways and Its Influence on the Interpretation of Biomedical Proteomics Data Sets

J Proteome Res. 2018 Nov 2;17(11):3801-3809. doi: 10.1021/acs.jproteome.8b00464. Epub 2018 Oct 24.

Abstract

Biochemical pathways are commonly used as a reference to conduct functional analysis on biomedical omics data sets, where experimental results are mapped to knowledgebases comprising known molecular interactions collected from the literature. Due to their central role, the content of the functional knowledgebases directly influences the outcome of pathway analyses. In this study, we investigate the structure of the current pathway knowledge, as exemplified by Reactome, discuss the consequences for biological interpretation, and outline possible improvements in the use of pathway knowledgebases. By providing a view of the underlying protein interaction network, we aim to help pathway analysis users manage their expectations and better identify possible artifacts in the results.

Keywords: pathway analysis; protein networks; protein−protein interactions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Databases, Protein
  • Humans
  • Knowledge Bases
  • Lymphocytes / cytology
  • Lymphocytes / metabolism*
  • Metabolic Networks and Pathways / physiology
  • Myeloid Cells / cytology
  • Myeloid Cells / metabolism*
  • Protein Interaction Mapping / methods*
  • Protein Interaction Maps
  • Proteomics / methods*