著者
岡田 随象
出版者
公益社団法人 日本生体医工学会
雑誌
生体医工学 (ISSN:1347443X)
巻号頁・発行日
vol.55, no.4, pp.165-172, 2017-08-10 (Released:2018-01-23)
参考文献数
20

Recent development of high throughput genome sequence technologies, such as next generation sequencer (NGS) and single nucleotide polymorphism (SNP) microarray, provides “flood” of human genome data. Large-scale human genetic studies incorporating more than 100,000 subjects have identified thousands of genetic variants with causal risk of human diseases. To handle such BIG data, sophisticated computational and statistical approaches are required. While construction of in silico pipelines to translate NGS raw reads to human genome variations is necessary, development of further strategies to interpret human genome data and understand disease biology elucidation and novel drug discovery is becoming more and more important. Statistical genetics is a research field that evaluates causality between human genetic and phenotypic variations, and considered as a promising tool to translationally connect human genome data with a variety of biological and medical resources. In this review, we highlight a basic theory, latest updates, and future directions of human genome data analysis with a series of introductory examples.

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解説特集:医療ビッグデータの可能性と現状の取り組み 遺伝統計学によるゲノムデータ解析 55_165.pdf https://t.co/QWkmqpv1g4
SNPによる主成分分析により出身地や人種背景を明確にする方法 https://t.co/z4PYjCkXcX https://t.co/7o74WfXPK2
あとで読む https://t.co/ZQZgw3e0jD

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