Large-Scale Analysis of Genetic and Clinical Patient Data

被引:13
|
作者
Ritchie, Marylyn D. [1 ,2 ]
机构
[1] Univ Penn, Dept Genet, Philadelphia, PA 19104 USA
[2] Univ Penn, Inst Biomed Informat, Perelman Sch Med, Philadelphia, PA 19104 USA
关键词
genetics; genomics; electronic health records; machine learning; phenomics; GWAS; PheWAS;
D O I
10.1146/annurev-biodatasci-080917-013508
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Biomedical data science has experienced an explosion of new data over the past decade. Abundant genetic and genomic data are increasingly available in large, diverse data sets due to the maturation of modern molecular technologies. Along with these molecular data, dense, rich phenotypic data are also available on comprehensive clinical data sets from health care provider organizations, clinical trials, population health registries, and epidemiologic studies. The methods and approaches for interrogating these large genetic/genomic and clinical data sets continue to evolve rapidly, as our understanding of the questions and challenges continue to emerge. In this review, the state-of-the-art methodologies for genetic/genomic analysis along with complex phenomics will be discussed. This field is changing and adapting to the novel data types made available, as well as technological advances in computation and machine learning. Thus, I will also discuss the future challenges in this exciting and innovative space. The promises of precision medicine rely heavily on the ability to marry complex genetic/genomic data with clinical phenotypes in meaningful ways.
引用
收藏
页码:263 / 274
页数:12
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