Developing Algorithms for Identifying Gene Modules in Single-Cell RNA-Seq Using Signed Graphs

• Project/Area Number: 24K18100
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 43060:System genome science-related
• Research Institution: The University of Tokyo
• Principal Investigator: Nagai LuisAugustoEijy 東京大学, 定量生命科学研究所, 助教 (50866689)
• Project Period (FY): 2024-04-01 – 2027-03-31
• Project Status: Granted (Fiscal Year 2024)
• Budget Amount: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000); Fiscal Year 2026: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000); Fiscal Year 2025: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000); Fiscal Year 2024: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
• Keywords: Signed networks / Community detection / Gene co-expression / Single-cell

Outline of Research at the Start

Single-cell gene co-expression networks (scGCN) provide a comprehensive view of cellular diversity at the single-cell level. I aim to develop computational methods for identifying gene modules using signed networks. My approach incorporates both positively and negatively correlated gene pairs to construct signed graphs, thereby enhancing scGCN network analysis. The outcomes from this research can bridge current methodological gaps, offering improved tools for data interpretation and downstream analyses.