Thomas C. Markello, David R. Adams
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引用次数: 4
Abstract
The analysis of genome-scale sequence data can be defined as the interrogation of a complete set of genetic instructions in a search for individual loci that produce or contribute to a pathological state. Bioinformatic analysis of sequence data requires sufficient discriminant power to find this needle in a haystack. Current approaches make choices about selectivity and specificity thresholds, and the quality, quantity, and completeness of the data in these analyses. There are many software tools available for individual, analytic component-tasks, including commercial and open-source options. Three major types of techniques have been included in most published exome projects to date: frequency/population genetic analysis, inheritance state consistency, and predictions of deleteriousness. The required infrastructure and use of each technique during analysis of genomic sequence data for clinical and research applications are discussed. Future developments will alter the strategies and sequence of using these tools and are also discussed. Curr. Protoc. Hum. Genet. 79:6.13.1-6.13.19. © 2013 by John Wiley & Sons, Inc.
基因组级测序鉴定孟德尔疾病相关基因
基因组规模序列数据的分析可以定义为在寻找产生或促成病理状态的单个位点时对一套完整的遗传指令的询问。序列数据的生物信息学分析需要足够的判别能力才能在大海捞针中找到这一针。目前的方法选择选择性和特异性阈值,以及这些分析中数据的质量、数量和完整性。有许多软件工具可用于单独的分析组件任务,包括商业和开源选项。迄今为止,在大多数已发表的外显子组项目中包含了三种主要类型的技术:频率/群体遗传分析、遗传状态一致性和有害性预测。在临床和研究应用的基因组序列数据分析过程中,讨论了所需的基础设施和每种技术的使用。未来的发展将改变使用这些工具的策略和顺序,并进行了讨论。咕咕叫。Protoc。嗡嗡声。79:6.13.1-6.13.19麝猫。©2013 by John Wiley &儿子,Inc。
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