In this course we will use R and the Seurat package to introduce the basic analysis steps and quality controls for single-cell RNA data. The target audience are PhD students and post-docs who have previous experience with R language.
Seurat is an R package designed for QC, analysis, and exploration of single-cell RNA-seq data. Seurat aims to enable users to identify and interpret sources of heterogeneity from single-cell transcriptomic measurements, and to integrate diverse types of single-cell data. All methods emphasize clear, attractive, and interpretable visualizations. Seurat is developed and maintained by the Satija lab and is released under the MIT license.
Goal: After the course, you will understand the challenges of single-cell RNA datasets, be able to conduct quality control of such data, and use Seurat to conduct your own analysis.
This is a hands-on course and requires (1) a
WLAN-capable laptop with Internet access (your device needs to be
registered with Core-IT). (2) An account for Workbench. We will use
the Rstudio server at the MPI-IE. If you do not have an account yet, you
will need to request a ‘linux’ account from core-IT (please do so well
before the course starts). We will be using R 4.2.3,
Bioconductor 3.16, and Seurat 5.0.2 during
this course.
Even though a simple laptop may not be powerful enough to handle larger analysis, you can use a local installation of R as well. Download it from here for your platform: Linux, Mac, Windows.
Some previous knowledge is assumed:
R-language: has been covered by our introductory course.
Bulk RNA-seq: has been covered by our introductory course.
Your keyboard! Special characters will be needed throughout the course, e.g. $ , | , [, ], {, }, >, <, #, ~, &, ^, %, !, ?
Course language: English