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SIGNAL: A web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection
Samuel Katz1, Jian Song2, Kyle P Webb2
1NIAID, National Institutes of Health, Laboratory of Immune System Biology, Bethesda, MD 20892, USA; University of Cambridge, Department of Veterinary Medicine, Cambridge, UK.
Cell Systems
|April 25, 2021
Summary
This study introduces SIGNAL, a new method to improve gene prioritization in omics studies by integrating pathway and network analysis. This approach overcomes limitations of existing methods, enhancing the efficiency of biological research.
Area of Science:
- Bioinformatics
- Systems Biology
- Genomics
Background:
- Hit selection from high-throughput assays is a bottleneck in omics studies.
- Current methods (cutoffs, pathway enrichment, network analysis) have analytical trade-offs and limited overlap in results.
- Lack of systematic integration leads to inefficiencies in secondary validation.
Purpose of the Study:
- To characterize complementary contributions of existing gene prioritization methods.
- To develop an optimal framework for integrating these methods.
- To introduce SIGNAL (Selection by Iterative Pathway Group and Network Analysis Looping) for optimized gene prioritization.
Main Methods:
- Comparative analysis of parallel independent studies as a benchmark.
- Development of an integrated, iterative approach combining pathway and network methods.
- SIGNAL framework utilizes iterative pathway group and network analysis looping.
Main Results:
- Characterization of complementary contributions of individual gene prioritization approaches.
- Demonstration of an optimal framework for integrating pathway and network methods.
- SIGNAL provides an optimized approach to gene prioritization.
Conclusions:
- SIGNAL offers an integrated, iterative solution to optimize gene prioritization in omics studies.
- The SIGNAL web application (https://signal.niaid.nih.gov) is user-friendly and accessible.
- This approach addresses limitations of existing methods, improving efficiency and reducing validation costs.
