Introduction to Transcriptomics

Undergraduate / Graduate

Transcriptomics is the study of the transcriptome -the complete set of RNA or transcripts that are produced by the genome, using high-throughput methods. In this course, students will learn about modern techniques used to capture and analyze mRNA and the connections of transcriptomics to epi-genomics (study of the epi-genome) and proteomics (study of proteins). The course will be divided into three parts: 1) Introduction of technologies that generate transcriptomics data, 2) Statistical analysis of the data, and 3) Case studies and applications. A range of topics relevant to the current practices in the field will be discussed, including introduction to microarrays, Next-Generation Sequencing (NGS), bulk and single-cell RNA processing, machine learning techniques used in data analyses, data pre-processing, differential expression analysis, and correcting batch effects and other experimental artifacts. Students will obtain hands-on experience in downloading public-domain data and performing analyses using different packages written in R and Python. After taking the class, students will have a working knowledge of the field and acquire experience in RNA-seq data analyses that are currently used in research labs. We will also organize visits to research laboratories and sequencing facility for the students to observe experimental workflows used in cutting-edge research.