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  1. C100 医学部/医学系研究科
  2. C100a 雑誌掲載論文
  3. 学術雑誌

Exploring predictive biomarkers from clinical genome-wide association studies via multidimensional hierarchical mixture models

http://hdl.handle.net/2237/00030227
http://hdl.handle.net/2237/00030227
371a70fe-e592-4f51-94c3-8e54e37ba28a
名前 / ファイル ライセンス アクション
manuscript.pdf manuscript (641.1 kB)
supplementary supplementary data (567.5 kB)
supplementary supplementary notes (276.4 kB)
table table s1 (86.1 kB)
table table s2 (85.7 kB)
table table s3 (78.7 kB)
table table s4 (76.9 kB)
table table s5 (77.6 kB)
table table s6 (84.1 kB)
table table s7 (80.2 kB)
table table s8 (77.1 kB)
table table s9 (76.9 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2019-05-15
タイトル
タイトル Exploring predictive biomarkers from clinical genome-wide association studies via multidimensional hierarchical mixture models
言語 en
著者 Otani, Takahiro

× Otani, Takahiro

WEKO 91285

en Otani, Takahiro

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Noma, Hisashi

× Noma, Hisashi

WEKO 91286

en Noma, Hisashi

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Sugasawa, Shonosuke

× Sugasawa, Shonosuke

WEKO 91287

en Sugasawa, Shonosuke

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Kuchiba, Aya

× Kuchiba, Aya

WEKO 91288

en Kuchiba, Aya

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Goto, Atsushi

× Goto, Atsushi

WEKO 91289

en Goto, Atsushi

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Yamaji, Taiki

× Yamaji, Taiki

WEKO 91290

en Yamaji, Taiki

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Kochi, Yuta

× Kochi, Yuta

WEKO 91291

en Kochi, Yuta

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Iwasaki, Motoki

× Iwasaki, Motoki

WEKO 91292

en Iwasaki, Motoki

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Matsui, Shigeyuki

× Matsui, Shigeyuki

WEKO 91293

en Matsui, Shigeyuki

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Tsunoda, Tatsuhiko

× Tsunoda, Tatsuhiko

WEKO 91294

en Tsunoda, Tatsuhiko

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アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
キーワード
主題Scheme Other
主題 Clinical trials
キーワード
主題Scheme Other
主題 Genome-wide association studies
キーワード
主題Scheme Other
主題 Predictive markers
抄録
内容記述 Although the detection of predictive biomarkers is of particular importance for the development of accurate molecular diagnostics, conventional statistical analyses based on gene-by-treatment interaction tests lack sufficient statistical power for this purpose, especially in large-scale clinical genome-wide studies that require an adjustment for multiplicity of a huge number of tests. Here we demonstrate an alternative efficient multi-subgroup screening method using multidimensional hierarchical mixture models developed to overcome this issue, with application to stroke and breast cancer randomized clinical trials with genomic data. We show that estimated effect size distributions of single nucleotide polymorphisms (SNPs) associated with outcomes, which could provide clues for exploring predictive biomarkers, optimizing individualized treatments, and understanding biological mechanisms of diseases. Furthermore, using this method we detected three new SNPs that are associated with blood homocysteine levels, which are strongly associated with the risk of stroke. We also detected six new SNPs that are associated with progression-free survival in breast cancer patients.
言語 en
内容記述タイプ Abstract
内容記述
内容記述 ファイル公開:2019/07/01
言語 ja
内容記述タイプ Other
出版者
言語 en
出版者 nature
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1038/s41431-018-0251-y
ISSN(print)
収録物識別子タイプ PISSN
収録物識別子 1018-4813
書誌情報 en : European Journal of Human Genetics

巻 27, 号 1, p. 140-149, 発行日 2019-01
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