Recent advances in molecular biology, microfluidics, and computation have transformed the growing field of single-cell RNA sequencing (scRNA-seq). In addition, new approaches now encompass diverse characterization of a single cell’s such as: chromatin accessibility, spatial positioning and immunophenotype. The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data.
This course is an introduction to basic approaches in single cell RNA-sequencing (scRNA-seq) data analysis and in combination with additional modalities. It will include hands-on exercises of common bioinformatics analysis workflows.
Experience in R programming and in analysis of bulk RNA-Seq is required.
We will cover the following topics:
- Introduction to Single cell technologies
- Analysing gene expression (GEX) from single cells with Cell Ranger (using Chromium 10X)
- Quality control measures, normalization, clustering and more using R package Seurat.
- Downstream analysis of gene expression data: annotating clusters, trajectories.
- Analysing multiome data i.e. GEX & ATAC-Seq using R package Signac
- Introduction to spatial transcriptomics