Introduction to RNA-Seq
This four-day course provides an introduction to methods for analysis of RNA-seq data. A typical RNA-seq workflow will be featured, starting from quality assessment of raw data, mapping (bwa, kallisto), differential expression analysis (DESeq2), and downstream analyses and visualization. The course also describes analysis methods for dealing with single-cell RNA-Seq data. Participants will gain hands-on experience using these tools in a Linux command line environment.
Preferred or Prerequisite Skills:
None
Computer Requirement:
Students should have their own laptop computer. UT EID is required for wireless access on campus. Please be sure you know both your UT EID when you come to class. To obtain a UT EID, go here.
Dhivya Arasappan (Co-Director, Bioinformatics Consulting Group, CBRS)
Dhivya Arasappan has over 15 years experience analyzing NGS data from multiple platforms. Her areas of expertise include RNA-Seq analysis (specifically involving large-scale brain expression datasets and coexpression network analysis), de novo genome assembly (particularly using hybrid sequencing data) and benchmarking of bioinformatics tools. She is the research educator for the Big Data in Biology Freshman Research Initiative stream.
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