2021 Fiscal Year Final Research Report
Development of cell trajectory inference and comparison algorithm based on single-cell omics data
Project/Area Number |
19K20399
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 62010:Life, health and medical informatics-related
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Research Institution | Kyoto University |
Principal Investigator |
Mori Tomoya 京都大学, 化学研究所, 助教 (50795333)
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Project Period (FY) |
2019-04-01 – 2022-03-31
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Keywords | 細胞系譜比較 / 細胞系譜推定 / シングルセル解析 / 木のアラインメント / 木の編集距離 / 機能遺伝子群解析 |
Outline of Final Research Achievements |
In this study, we have developed an algorithm for cell trajectory inference and comparison with high accuracy based on single-cell gene expression data. We applied this algorithm to single-cell human fibroblast and human skeletal muscle myoblast data, and after finding the correspondence of cell clusters between the two datasets using tree alignment, a pseudotime comparison was performed based on the dynamic time warping for the paths on the alignment. As a result, it was confirmed that the analysis results were consistent with existing reports. Its effectiveness was also confirmed in the experiments using synthetic data and real data of human bone marrow. In addition, we compared it with other methods and performed functional gene set analysis, and then submitted a paper together with consideration of the usefulness of this method and biological interpretation of the results.
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Free Research Field |
バイオインフォマティクス
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Academic Significance and Societal Importance of the Research Achievements |
本研究課題の目的は,単一細胞遺伝子発現データに基づいて細胞系譜を推定し,それらの比較を通じて生物学的および医学的知見を獲得するための高速かつ高精度な統合解析アルゴリズムを開発することである。本研究課題で開発した手法をさらに発展させ,細胞間の系統関係をより詳細なレベルで明らかにすることができれば,正常組織の発達,恒常性の維持機能,発達障害,そして癌などの病理について重要な情報を提供することができるだけでなく,分化性能の良いiPS細胞を選別することや細胞が正常に分化しない場合の原因究明などに役立つと考えられるため,再生医療研究の一助となることが期待される.
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