Detecting Signaling Pathway Activation Using SVD Regression
Author Information
Author(s): Liu Zhandong, Wang Min, Alvarez James V, Bonney Megan E, Chen Chien-chung, D'Cruz Celina, Pan Tien-chi, Tadesse Mahlet G, Chodosh Lewis A
Primary Institution: University of Pennsylvania
Hypothesis
Can singular value decomposition-based regression detect the activation of endogenous signaling pathways in vivo?
Conclusion
The study demonstrates that singular value decomposition regression can effectively detect the activation of endogenous signaling pathways in vivo.
Supporting Evidence
- SVD regression can detect the activation of dominant oncogenic signaling pathways.
- The study confirmed that Ras activation leads to TGFβ pathway activation.
- Biochemical studies validated the computational predictions made by SVD regression.
- Signaling pathway activation was detected in both mouse models and human samples.
Takeaway
Researchers used a special math method to see how two important cell signaling pathways talk to each other in mice. They found that when one pathway is turned on, it can also turn on the other.
Methodology
The study used singular value decomposition-based regression to analyze gene expression data from mouse models.
Limitations
The study primarily focused on specific pathways and may not generalize to all signaling pathways.
Participant Demographics
The study involved transgenic mice models.
Statistical Information
P-Value
1.2 × 10-107
Statistical Significance
p<0.01
Digital Object Identifier (DOI)
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