Journal
STAR PROTOCOLS
Volume 2, Issue 4, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.xpro.2021.100955
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Funding
- DARPA under the Big Mechanism Program [W911NF-14- C-0119]
- U.S. Army Research Office [ACC-APG_RTP W911NF]
- NIH [R01HL146549, U41HG006623, P41GM103504]
- Ruth L. Kirschstein National Research Service Award [F32 CA192901]
- MD Anderson Cancer Center [P30 CA016672]
- OCRA collaborative research grant
- Scientific and Technological Research Council of Turkey [118E131]
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CausalPath evaluates proteomic measurements against biological pathways to infer causality between changes in measured features, reporting statistically significant relationships supported by proteomic profiles to explain observed patterns.
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 statisti-cal 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).
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