Statistical Analysis of single cell RNA-seq (scRNA-seq) Data

CSTAT Seminar series: Statistical Analysis of RNA-seq Data  Part 2

Dr. Arash Yunesi, Michigan State University, CSTAT

scRNA-seq is currently the most widely used technology in this group. It differs from the traditional bulk RNA-seq in that cells are separated, tagged, and sequenced one by one, giving us a more detailed information of the inner workings of cells and tissue. scRNA-seq produces a large matrix of data from each sample and it provides opportunities for more sophisticated and complex analyses. In this workshop, we will cover preprocessing, quality control, variable gene selection, variance stabilizing transformations, dimensional reduction, unsupervised clustering, annotations, marker gene selection, and data integration for scRNA-seq data. For this workshop we will focus on Seurat, a specialized package to work with scRNA-seq data and perform various analyses and visualizations. Bring your own laptop.

This Workshop will have a non-refundable $10 registration fee to reserve your spot, paid through Eventbrite at registration. 

Registration not yet open