Single cell technologies are extremely powerful in unraveling heterogeneity within multicellular systems, and are increasingly applied across all biological systems. Different cellular macromolecules (i.e. DNA, RNA, Chromatin accessibility, Proteins etc.,) within individual cells are profiled at high throughput through a combination of novel methods, different technologies and a strong data analysis component.

This course aims to build a basic understanding of different technologies and approaches used to isolate single-cells, perform different workflows to extract and measure cellular macromolecules (DNA, chromatin, proteins) at single-cell level through high-throughput technologies within mammalian cell systems. This course will also have a data analysis component and provide the students with skills to analyze, understand and interpret different data analysis steps (quality control, dimensionality reduction, clustering etc.).

The students will obtain critical knowledge for evaluating the strengths and weaknesses of various single cell technologies, conduct independent data interpretation on highly multi-dimensional datasets, and appreciate the impact of such technologies in identifying cellular heterogeneity both in health and disease.