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Single-cell RNA-seq data analysis workshop

Learning Objectives


  1. Follow the instructions linked here to download R and RStudio + Install Packages from CRAN and Bioconductor

  2. Download this project


Part 1

  1. Introduction to scRNA-seq
  2. Raw data to count matrix

Part II

  1. Quality control set-up
  2. Quality control
  3. Overview of Clustering Workflow
  4. Theory of PCA
  5. Normalization and regressing out unwanted variation

Part III

  1. Integration
  2. Clustering
  3. Clustering quality control
  4. Marker identification

Building on this workshop


We have covered the analysis steps in quite a bit of detail for scRNA-seq exploration of cellular heterogeneity using the Seurat package. For more information on topics covered, we encourage you to take a look at the following resources:

These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.