2021 Fiscal Year Final Research Report
Re-annotation of large-scale human genome data by integration of statistical genetics and operations research
| Project/Area Number |
20K21834
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Review Section |
Medium-sized Section 62:Applied informatics and related fields
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| Research Institution | Osaka University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
垣村 尚徳 慶應義塾大学, 理工学部(矢上), 准教授 (30508180)
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| Project Period (FY) |
2020-07-30 – 2022-03-31
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| Keywords | 遺伝統計学 / 最適化理論 |
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| Outline of Final Research Achievements |
Large-scale human genome data has two major characteristics; (i) limited fractions of the human genome variations only affects human disease risk, (ii) numbers of the human genome variations are much larger than those of samples (i.e., P>>N problem). Statistical genetics handles human population genome data as input, which can be described as simple graphs. We considered that these graphs can be solved by operations researches. This project aims re-annotation of large-scale human genome data by integration of statistical genetics and operations research through iterdisciplinary cooperative studies.
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| Free Research Field |
遺伝統計学
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| Academic Significance and Societal Importance of the Research Achievements |
遺伝統計学と最適化理論は共通した理論的背景を有するも、異なる学問分野として捉えられてきた。本研究は、大規模疾患ゲノム情報をシンプルな行列・グラフ情報として捉えることにより、る数理理論の応用研究の題材となることを示し、学際連携の新たな可能性を切り拓いたものとして学術的な意義を有すると考えられる。今後、解析アルゴリズムのスケーラビリティーの獲得と高速計算化を進めることで、より汎用性の高い情報解析ツールとしての実装が可能になると期待される。
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