一个全面的生物信息学方法分析变体:变体调用,注释和优先级
Merve Nur Koroglu1, Kaya Bilguvar2,3
1Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.
Methods in molecular biology (Clifton, N.J.)
|January 2, 2025
概括
下一代测序 (NGS) 提供了快速的DNA/RNA测序,彻底改变了基因组学和癌症研究. 本章详细介绍了分析这些高通量技术产生的庞大的基因组数据的计算方法.
科学领域:
- 基因组学和生物信息学
- 分子生物学分子生物学
- 计算生物学 计算生物学
背景情况:
- 下一代测序 (NGS) 技术使得DNA和RNA的快速,经济高效的测序成为可能.
- 这些高通量方法已经改变了基因组学,转录组学和蛋白质组学.
- 在癌症研究中,NGS对于推进临床诊断和治疗至关重要.
研究的目的:
- 为基因组数据分析提供全面的计算方法.
- 详细介绍大型基因组数据集所需的基本分析步骤.
- 为了解决对高效生物信息学方法的需求,以解释NGS数据.
主要方法:
- 利用先进的生物信息管道进行基因组数据处理.
- 实施高效的计算资源来处理大型数据集.
- 描述DNA和RNA测序数据的系统分析步骤.
主要成果:
- 证明了基因组数据分析的详细计算方法的有效性.
- 促进了NGS产生的大规模基因组数据的高效解释.
- 实现了理解基因组变异及其影响的进步.
结论:
- 为了最大限度地利用NGS数据,全面的计算策略至关重要.
- 有效的生物信息学分析是释放高通量测序在研究和临床应用中的潜力的关键.
- 本章为研究人员分析复杂的基因组数据集提供了基本指南.
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