Next generation DNA sequencing data analysis and its application in clinical genomics

Next-generation sequencing (NGS) has transformed genomics by enabling rapid, high-throughput analysis of DNA and RNA, driving significant progress across multiple fields, such as cancer research, rare disease diagnosis, and personalized medicine. This review discusses the wide-ranging applications of NGS, particularly in identifying genetic variants that guide the development of targeted therapies, improving patient outcomes. The NGS workflow involves crucial steps including data quality control, sequence alignment, and variant calling, supported by both open-source and commercial tools. Cloud-based platforms have further streamlined the storage, management, and processing of the vast datasets generated by NGS technologies. As NGS continues to evolve, ethical challenges, especially concerning genomic data privacy and informed consent, remain critical considerations. Looking ahead, the integration of multi-omics data and the advent of single-cell sequencing hold the potential to deepen our understanding of complex biological processes. Essential databases like dbSNP, COSMIC, and The Cancer Genome Atlas are key resources for interpreting NGS findings and their clinical significance. By effectively utilizing these tools and datasets, researchers can generate new genetic insights with far-reaching implications for advancing human health and understanding disease mechanisms.