Analyzing causal relationships in proteomic profiles using CausalPath

Date

2021-12-17

Editor(s)

Advisor

Supervisor

Co-Advisor

Co-Supervisor

Instructor

Source Title

STAR Protocols

Print ISSN

2666-1667

Electronic ISSN

Publisher

Cell Press

Volume

2

Issue

4

Pages

1 - 12

Language

English

Journal Title

Journal ISSN

Volume Title

Series

Abstract

CausalPath (causalpath.org) 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.

Course

Other identifiers

Book Title

Citation