Introduction to scRNA-seq data analysis and interpretation using Seurat

Yujie Guo, research assistant in Dr. Heng Li's lab. She's working on cancer genome assembly.
Seurat is an R package designed for QC, analysis, and exploration of single-cell RNA-seq data. It has been widely used in both dry lab and wet lab settings for its robustness and scalability. In this coding workshop, we will demonstrate the workflow of Seurat, use published matched tumor-normal data, and have hands-on experience of analyzing and interpreting such information.
Moduled Scripts: github.com/magspho/DS_seurat_...
Our #DataScience Training Sessions offer hands-on training in #statistics, #computationalbiology and #machinelearning by experts at the Department of Data Science at Dana-Farber Cancer Institute.