Transcriptome Data Analysis

Advances in transcriptomics have revolutionized the fields of biology and medicine. Use of high-throughput sequencing technologies has resulted in mountains of transcriptomic data, which has necessitated the development of efficient methods for their analysis and interpretation. This volume presents a comprehensive description of the advances in transcriptomics, with a focus on methods and pipelines for transcriptome data analysis. In addition to the step-by-step description of well-established RNA sequencing (RNA-Seq) data analysis protocols, specialized pipelines have also been described, such as multi-omics data integration and analysis, gene interaction network construction, single-cell trajectory inference, detection of structural variants, and application of machine learning, to mention a few. This Methods in Molecular Biology series provides a useful resource for educators and researchers to help familiarize them with the new developments in the field, learn usage of the protocols for transcriptome data analysis, and implement the tools or pipelines to address relevant problems of their interest.