生物
DNA测序
孟德尔遗传
人类遗传学
遗传学
计算生物学
外显子组测序
工作流程
人类疾病
全基因组测序
突变
基因
基因组
计算机科学
数据库
作者
David B. Goldstein,Andrew S. Allen,Jonathan Sebat,Elliott H. Margulies,Steven Petrou,Slavé Petrovski,Shamil Sunyaev
摘要
Next-generation sequencing is now poised for the discovery of genetic variants involved in common and rare diseases. Here, the authors present considerations for the workflow of these studies in order to identify true associations of disease and mutation. Next-generation sequencing is becoming the primary discovery tool in human genetics. There have been many clear successes in identifying genes that are responsible for Mendelian diseases, and sequencing approaches are now poised to identify the mutations that cause undiagnosed childhood genetic diseases and those that predispose individuals to more common complex diseases. There are, however, growing concerns that the complexity and magnitude of complete sequence data could lead to an explosion of weakly justified claims of association between genetic variants and disease. Here, we provide an overview of the basic workflow in next-generation sequencing studies and emphasize, where possible, measures and considerations that facilitate accurate inferences from human sequencing studies.
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