Single-cell analysis for functional genomics of disease

BMI 710 Subject & Catalog Number

Description

Single-cell technologies promise unparalleled insights into human biology, but first, these data require a new computational and statistical toolkit.  In this course, we will compare single-cell and bulk data analysis paradigms, and explore new methods to quality control, analyze, and interpret single-cell-RNA-sequencing data.  Students will learn about single-cell technologies and experimental design, build pipelines to process sequencing data, and use R packages for quality control and analysis.  Students will learn about frameworks for interpreting single-cell data - eg., trajectories, differential abundance - and use them to answer biological questions with single-cell datasets in diverse domains.  We will conclude by exploring the application of single-cell technologies to disease cohorts with spatial profiling, reference mapping, and multimodal approaches.  Class activities will include lectures, coding activities, and paper discussions.