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This course will introduce computational tools used in the field of transcriptomics to analyze the genes and transcripts expressed in a living cell. Lectures will cover different practical ways to analyze large data sets generated by high-throughput RNA sequencing (RNA-Seq) experiments, including alignment, assembly, and quantification. The students will learn how to use RNA-seq to answer questions such as: what is the complete set of human genes? How do we reconstruct the splice variants that are transcribed in different cell types and conditions? How do we compute which genes are differentially expressed between different RNA-seq datasets? Prerequisites: (1) Familiarity with Python or Perl, (2) the Unix command-line environment, and (3) a basic understanding of programming in R.