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候选基因关联研究:实用计算工具的综合指南。

Candidate gene association studies: a comprehensive guide to useful in silico tools.

机构信息

Australian Prostate Cancer Research Centre - Queensland, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD 4059, Australia.

出版信息

BMC Genet. 2013 May 9;14:39. doi: 10.1186/1471-2156-14-39.

Abstract

The candidate gene approach has been a pioneer in the field of genetic epidemiology, identifying risk alleles and their association with clinical traits. With the advent of rapidly changing technology, there has been an explosion of in silico tools available to researchers, giving them fast, efficient resources and reliable strategies important to find casual gene variants for candidate or genome wide association studies (GWAS). In this review, following a description of candidate gene prioritisation, we summarise the approaches to single nucleotide polymorphism (SNP) prioritisation and discuss the tools available to assess functional relevance of the risk variant with consideration to its genomic location. The strategy and the tools discussed are applicable to any study investigating genetic risk factors associated with a particular disease. Some of the tools are also applicable for the functional validation of variants relevant to the era of GWAS and next generation sequencing (NGS).

摘要

候选基因方法一直是遗传流行病学领域的先驱,确定了风险等位基因及其与临床特征的关联。随着技术的快速发展,研究人员可获得大量的计算机工具,这些工具为他们提供了快速、高效的资源和可靠的策略,对于候选基因或全基因组关联研究(GWAS)寻找偶然的基因变异至关重要。在描述候选基因优先级之后,我们总结了单核苷酸多态性(SNP)优先级的方法,并讨论了可用的工具,以评估风险变异的功能相关性,同时考虑其基因组位置。所讨论的策略和工具适用于任何研究遗传危险因素与特定疾病相关的研究。其中一些工具也适用于与 GWAS 和下一代测序(NGS)相关的变体的功能验证。

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