Koroglu Merve Nur, Bilguvar Kaya
Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.
Yale School of Medicine, Yale University, New Haven, CT, USA.
Methods Mol Biol. 2025;2889:207-233. doi: 10.1007/978-1-0716-4322-8_15.
Next-Generation Sequencing (NGS), also known as high-throughput sequencing technologies, has enabled rapid and efficient sequencing of large amounts of DNA and RNA. These technologies have revolutionized the field of genomics, transcriptomics, and proteomics and have been widely used in cancer research, leading to advances in clinical diagnosis and treatment. Improvements in the NGS technologies enabled millions of fragments to be sequenced simultaneously in a time- and cost-effective manner and resulted in large amount of genomic data which require efficient analysis methods. Analysis of the genomic data requires both efficient computer resources and bioinformatics approaches. This chapter details a comprehensive computational approach and analysis steps for genomic data analysis.
下一代测序（NGS），也被称为高通量测序技术，能够对大量DNA和RNA进行快速高效的测序。这些技术彻底改变了基因组学、转录组学和蛋白质组学领域，并已广泛应用于癌症研究，推动了临床诊断和治疗的进步。NGS技术的改进使得数百万个片段能够以具有时间和成本效益的方式同时进行测序，并产生了大量需要高效分析方法的基因组数据。基因组数据分析既需要高效的计算机资源，也需要生物信息学方法。本章详细介绍了一种用于基因组数据分析的全面计算方法和分析步骤。
