2009 Fiscal Year Final Research Report
Robust inference and its application to genome data
Project/Area Number |
19700270
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Single-year Grants |
Research Field |
Statistical science
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Research Institution | The Institute of Statistical Mathematics |
Principal Investigator |
FUJISAWA Hironori The Institute of Statistical Mathematics, 数理・推論研究系, 准教授 (00301177)
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Project Period (FY) |
2007 – 2009
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Keywords | ロバスト推測 / 遺伝子発現データ / 一塩基多型 |
Research Abstract |
When outliers are present, many statistical methods lose the validity of the result for analyzing the data. The statistical method which gives the valid result even if outliers are present is called the robust inference. In particular, it is important to make a latent bias small even when outliers are present. I have discussed robust inference and applied the method to genome data.
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[Journal Article] SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip.2009
Author(s)
Fujisawa, H., Horiuchi, Y., Harushima, Y., Takada, T., Eguchi, S., Mochizuki, T., Sakaguchi, T., Shiroishi, T., Kurata, N.
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Journal Title
BMC Bioinformatics Vol.10,No.131
Peer Reviewed
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[Journal Article] Identifying haplotype block structure by using ancestor-derived model.2007
Author(s)
Fujisawa, H., Isomura, M., Eguchi, S., Ushijima, M., Miyata, S., Miki, Y., Matsuura, M.
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Journal Title
Journal of Human Genetics Vol.52
Pages: 738-746
Peer Reviewed
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