全基因组关联研究
计算生物学
遗传关联
鉴定(生物学)
疾病
基因组
生物
人类基因组
基因
遗传学
生物信息学
单核苷酸多态性
医学
基因型
病理
植物
作者
Tobias Wohland,Dorit Schleinitz
出处
期刊:Methods in molecular biology
日期:2018-01-01
被引量:1
标识
DOI:10.1007/978-1-4939-7471-9_7
摘要
Genome-wide association studies (GWAS) provide a hypothesis-free approach to discover genetic variants contributing to the risk of a certain disease or disease-related trait. Ongoing efforts to annotate the human genome have helped to localize disease-causing variants and point to mechanisms by which genetic variants might exert functional effects. By integrating bioinformatics approaches with in vivo and in vitro genomic strategies to predict and subsequently validate the functional roles of GWAS-identified variants, disease-related pathways can be characterized, providing new possibilities for therapeutic intervention. Here, we describe a basic workflow, from sample preparation to data analysis, for performing a GWAS to identify disease genes. We also discuss resources for the annotation and interpretation of GWAS results.
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