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RCDRank: a web server to prioritize regulated cell death modalities
Nan Zhou1, Tong Yin2,3, Huiran Sun2,3
1Research Center, The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, 510370, China.
Background:
Regulated cell death (RCD) maintains cellular homeostasis and tissue integrity, playing a pivotal role in both health and disease. A variety of RCD subroutines have been identified, each characterized by distinct molecular and morphological features. These cell death modalities do not operate in isolation. Instead, they interact with one another in complex ways. This interaction leads to crosstalk through interconnected and often overlapping signaling pathways. Multiple forms of RCD can coexist within the same disease, influencing various cell types or even the same cell type either synchronously or sequentially. Understanding the intricate dynamics of RCD is of high importance. However, it is challenging to discern the relative contribution of various RCD modalities within the specific biological context. This necessitates the development of advanced methodologies to systematically analyze the priority of RCD pathways in various cellular environments. MAIN: In the present study, we first created a manually curated collection of gene sets for 18 well-characterized RCD modes. We then estimated the significance of each RCD pathway by combining the results of seven gene set enrichment tests via the Tippet p-value combination approach. Afterward, the consensus of enrichment for each RCD pathway across tests was evaluated using robust rank aggregation. The priorities of RCD were subsequently resolved by considering both the combined p value and the consensus score. The reliability of the proposed approach was validated by applying it to explore the RCD modes in intracranial aneurysms. Finally, a user-friendly web application was created for researchers worldwide.
Conclusion:
Our study offers a new way to reveal complicated RCD modalities in specific biological settings. The web server is freely accessible at https://www.zhounan.org/rcdrank.
Insights
This study introduces a novel method to rank regulated cell death (RCD) pathways by analyzing gene sets and pathway interactions. A new web tool helps researchers prioritize RCD modalities in different biological contexts.
Area of Science:
- Cellular Biology
- Molecular Biology
- Bioinformatics
Background:
- Regulated cell death (RCD) is crucial for homeostasis and tissue integrity, involving diverse, interacting pathways.
- Understanding the complex interplay and relative importance of RCD modalities in disease is challenging.
- Existing methods struggle to systematically analyze RCD pathway priorities in specific biological contexts.
Purpose of the Study:
- To develop an advanced methodology for systematically analyzing and prioritizing regulated cell death (RCD) pathways.
- To create a user-friendly web application for researchers to explore RCD dynamics.
Main Methods:
- A manually curated collection of gene sets for 18 RCD modes was created.
- Seven gene set enrichment tests were combined using Tippet's p-value approach.
- Robust rank aggregation evaluated pathway consensus, with priorities determined by combined p-value and consensus score.
Main Results:
- A novel approach was developed to systematically rank and analyze 18 well-characterized RCD pathways.
- The method integrates multiple enrichment tests and rank aggregation for robust pathway prioritization.
- The approach was validated in the context of intracranial aneurysms, revealing complex RCD dynamics.
Conclusions:
- A new computational method and web server (RCRank) are available for dissecting complex RCD modalities in specific biological settings.
- The RCRank web server provides a valuable resource for researchers studying cell death pathways.
- This work facilitates a deeper understanding of RCD's role in health and disease.
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