Next-Generation Sequencing and Genomic Data Analysis

Next-generation sequencing (NGS) technologies have revolutionized the field of genomics, enabling rapid and cost-effective sequencing of DNA/RNA molecules at unprecedented scales. This chapter presents a comprehensive overview of NGS methodologies and genomic data analysis techniques, highlighting recent advancements and future prospects. We delve into the principles underlying NGS platforms, including Illumina sequencing, Ion Torrent sequencing, and Pacific Biosciences Single Molecule Real-Time (SMRT) sequencing, elucidating their strengths and limitations. In parallel, this abstract explores the challenges and opportunities in genomic data analysis, encompassing a spectrum of computational methods for data preprocessing, alignment, variant calling, and functional annotation. We emphasize the significance of bioinformatics pipelines in handling large-scale genomic datasets, integrating tools for quality control, read mapping, and variant detection. Furthermore, we elucidate the role of machine learning and artificial intelligence in genomic data analysis, elucidating their applications in genotype–phenotype associations, population genetics, and personalized medicine. Through this abstract, we aim to provide a roadmap for researchers and practitioners navigating the complex landscape of NGS and genomic data analysis, fostering a deeper understanding of the underlying technologies and methodologies driving genomic research in the next decade.