2016 Fiscal Year Final Research Report
Statistical methods for immuno-repertoire analysis based on TCR sequence data
| Project/Area Number |
15K14433
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
System genome science
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Co-Investigator(Renkei-kenkyūsha) |
Hori Shohei 国立研究開発法人理化学研究所, 統合生命医科学研究センター, チームリーダー (50392113)
Yokota Ryo 東京大学, 生産技術研究所, 特任研究員 (80733154)
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| Research Collaborator |
Katayama Yotaro
Kaminaga Yuki
Kaneko Kazumasa
Kajita Masashi
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| Project Period (FY) |
2015-04-01 – 2017-03-31
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| Keywords | T細胞 / T細胞受容体 / 免疫レパートリ / 免疫レパトア / 適応免疫 / 複雑系 / 次世代シーケンサー |
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| Outline of Final Research Achievements |
In order analyze the diversity of the T cells (repertoire), based on the information of the receptor (TCR) sequence of individual T cells obtained by the next generation sequencer, we constructed computational methods to clarify the hidden structure of immune repertoires.
A low dimensional structure of the data was extracted by projecting the data into a low dimensional space while keeping the similarity relation among TCR sequences. We also succeeded in quantifying the differences between different repertoire samples and in identifying the responsible sequences that make up the sample differences, by using the information-theoretic measure between the density distributions in the low dimensional space. We also confirmed that the relationship between samples obtained by our method not only provides consistent results with previous studies but also stable results even for higher dimensional and more sparse data sets. We also examined the effectiveness of hierarchical statistical models.
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| Free Research Field |
定量生物学
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