Teaching

G4017: Deep Sequencing - Fall 2021

Next-generation sequencing (NGS) has become ubiquitous in biomedical research with numerous applications. This course will provide an in-depth introduction to the principles of modern sequencing, key computational algorithms and statistical models, and applications in disease genetics, cancer, and fundamental biology. We will cover genome, exome, and transcriptome sequencing approaches. Emphasis will be placed on understanding the interplay between experimental design, data acquisition, and data analysis so that students can apply these powerful tools in their own research.

Main topics will include: 

1) History and development of modern sequencing technologies

2) Introduction to statistics and algorithms for processing and interpreting NGS data

3) Genome sequencing and genetics of Mendelian and complex diseases (analysis and laboratory techniques for whole genome and exome sequencing)

4) RNA-Seq and transcriptional regulation (analysis and laboratory techniques for expression profiling, CLIP-Seq, ribosome profiling, micro-RNA profiling, ChIP-Seq, DNase-Seq, ATAC-Seq)

5) Cancer genomics

6) Emerging third- and fourth-generation sequencing technologies and new tools for single cell analysis

The course will be offered through the Department of Biomedical Informatics.  It will be co-taught by Yufeng Shen, Chaolin Zhang, and Peter Sims.