Next-Generation Sequencing (NGS) has become the cornerstone of modern genomics and a catalyst for breakthroughs in molecular biology, biomedical research, and precision medicine. Its scalability, sensitivity, and throughput have enabled researchers to explore complex biological questions with unprecedented resolution—across single-cell biology, spatial and bulk transcriptomics, epigenomics, metagenomics, and clinical genomics.

At the same time, the rapid expansion of sequencing platforms (e.g., Illumina, Oxford Nanopore, PacBio), library preparation protocols, and data analysis pipelines has introduced significant complexity in selecting optimal workflows. As most emerging analytical approaches rely on high-quality NGS data, understanding the trade-offs, limitations, and performance of different technologies has become essential for robust, reproducible, and scalable experimental design.

This Methods Collection aims to provide a comprehensive, technically rigorous overview of the current NGS landscape. It will feature articles detailing benchmarking sequencing platforms, library construction and enrichment protocols, quality control measures, and computational analysis strategies, exploring innovative applications. Emphasis will be placed on comparative studies, best practices, and context-specific optimizations that support diverse research needs.

The collection brings together expert insights from the entire next-generation sequencing (NGS) workflow—covering sample preparation, sequencing, data analysis, and biological interpretation. It aims to serve as a practical and trustworthy resource for the research community. By emphasizing alternative methods and their respective trade-offs, it will support informed decision-making and the development of reproducible, efficient, and application-specific sequencing strategies. The goal of this initiative is to enhance transparency, promote compatibility across different platforms, and foster progress in both basic and translational research.