In terms of software, we are mainly using deeptools2, which is available to you by loading the “gencore” and “gencore_variant_detection” modules. We will also explore an alternative way of generating the CHiP-seq plots in R and Rstudio using the bioconductor package CoverageView.
As mentioned earlier, our exercise will focus on the data generated as part of the paper in (Xin et al). The data represents 2 conditions, knockout (KO) and wildtype (WT), with 2 different modifications, Brg1 and H3K9Me3. In addition, we have 1 Input for each of our conditions. So in total we have the 6 samples below,
The data can be found at,
Getting the data and creating your analysis directory
- Open up a terminal
- Log in to your HPC (Dalma)
- Change into your scratch directory
- Copy the datasets
1cp /scratch/gencore/datasets/chipseq_dataset.tar.gz .
- Untar the dataset and cd to the analysis directory.
12tar -xvf chipseq_dataset.tar.gzcd chipseq_analysis
- Change into the bigWigs directory
1ls -lah bigWigs