Analyzing causal relationships in proteomic profiles using CausalPath

STAR Protoc. 2021 Nov 23;2(4):100955. doi: 10.1016/j.xpro.2021.100955. eCollection 2021 Dec 17.


CausalPath ( evaluates proteomic measurements against prior knowledge of biological pathways and infers causality between changes in measured features, such as global protein and phospho-protein levels. It uses pathway resources to determine potential causality between observable omic features, which are called prior relations. The subset of the prior relations that are supported by the proteomic profiles are reported and evaluated for statistical significance. The end result is a network model of signaling that explains the patterns observed in the experimental dataset. For complete details on the use and execution of this protocol, please refer to Babur et al. (2021).

Keywords: Bioinformatics; Proteomics; Systems biology.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Causality
  • Databases, Protein
  • Humans
  • Protein Interaction Mapping / methods*
  • Proteins* / metabolism
  • Proteins* / physiology
  • Proteomics / methods*
  • Signal Transduction / physiology*
  • Software


  • Proteins