shRNA-seq and CRISPR-Cas9 genetic screen analysis using edgeR

This webpage provides code and data that demonstrates how to use the edgeR package to perform a differential representation analysis of shRNA-seq and sgRNA-seq screen data, as described in Dai et al. (2014) edgeR: a versatile tool for the analysis of shRNA-seq and CRISPR-Cas9 genetic screens, F1000Research, 3:95. Please cite this article if you make use of the pipeline we describe in your research.

Note I: The processAmplicons function referred to in version 2 of our paper replaces the processHairpinReads function from version 1.

Case study

The vignette for this case study (pdf)

The R code used in this case study


You must have R (version 4.0.3 or later) installed on your computer to run this case study.

You also need to install the edgeR (version 3.32.0 or later) and limma (version 3.46.0 or later) Bioconductor packages (available release 3.12). Type the following commands at the R command prompt to install these packages:

if (!requireNamespace("BiocManager", quietly = TRUE))

For information on our Galaxy tool see here.


This case study looks at data from 6 different screens. Gzipped archives of the data from each screen can be downloaded from the following links: Screen 1 (shRNA-seq) [5.1G], Screen 2 (shRNA-seq) [2.3G], Screen 3 (shRNA-seq) [8.4G], Zuber Screen (shRNA-seq) [62Kb], Screen 4 (CRISPR-Cas9) [11G], Shalem Screen (CRISPR-Cas9) [3.3Mb].

After downloading, uncompress and save these files to your current working directory. You should then be able to run the code provided above.


Matt Ritchie (mritchie at wehi dot edu dot au)