Bioinformatics Analysis of Transcriptomic Data (Bulk and scRNA-Seq) for Immuno-Oncology

Bioinformatics plays a pivotal role in immunology by enabling the analysis of large-scale datasets generated from high-throughput technologies, such as next-generation sequencing (NGS), single-cell RNA sequencing (scRNA-seq), and mass cytometry. These methods provide deep insights into immune system dynamics, helping to decode immune cell heterogeneity, gene expression patterns, and immune receptor repertoires. Key bioinformatics approaches include transcriptomic analysis to identify immune-related gene signatures, single-cell sequencing tools for profiling immune cell states, immune repertoire analysis to understand T-cell and B-cell diversity, and multiomics integration to uncover regulatory networks. By leveraging these methods, researchers can better understand immune responses in health and disease, identify therapeutic targets, and develop precision immunotherapies. This chapter will offer a comprehensive guide to the essential bioinformatics tools and techniques used in immunological research, facilitating effective data analysis and interpretation.