Analysis and Interpretation of Bulk RNA-Sequencing Data Using Bioconductor

Music City Center 

Room: CC-107A 

RNA sequencing (RNA-seq) has transformed the field of genomics over the past 15 years, enabling researchers to gain comprehensive insights into gene expression, transcriptome dynamics, and molecular pathways. Among high-throughput sequencing analyses, statistical analysis of RNA-seq data has become one of the most frequently performed tasks in computational biology. Bioconductor, an open-source software project, provides an extensive collection of tools tailored for analyzing genomic data, including RNA-seq datasets. In this Carpentries-style course, participants will learn to use state-of-the-art statistical software packages to develop the skills needed for RNA-seq data analysis within the Bioconductor ecosystem. Throughout the course, participants will delve into key aspects of RNA-seq analyses, such as data preprocessing, quality control, differential gene expression analysis, visualization, and gene set analysis. This course is specifically designed for early-career researchers and practitioners who are interested in mastering the fundamentals of an end-to-end RNA-seq analysis pipeline. A working knowledge of R programming and prior familiarity with the Bioconductor project are essential prerequisites for attendees. This course has been developed as part of the Bioconductor Global Training Carpentries Program, a collaborative effort to consolidate Bioconductor-focused training materials and establish a community of Bioconductor trainers and users. More information can be obtained from https://training.bioconductor.org/carpentry/.

Section on Statistics in Genomics and Genetics