Setup

In these tutorials we will be using the following software:

  • deepTools. Analysis suite for sequencing data. You can read about the installation in their documentation.

  • IGV. Integrative Genomics Viewer.

  • intervene. Easy to use R tool that allows to plot overlap between bed files. It can be installed through bioconda and pip (for me it worked using pip, but not conda though). Bedtools is a dependency. See more detailed info in the intervene documentation site.

  • R. ggplot2 and a couple Bioconductor R packages will be needed, mostly as dependencies: GenomicRanges, rtracklayer. Furthermore, the Spike-in tutorial requires some other packages: ChIPSeqSpike and BSgenome.Hsapiens.UCSC.hg38.

You can run R in any preferred way you have been running during this workshop. The dependencies are small so you probably have these packages installed. Most definitely these are available through Uppmax module system.

Bioconductor packages can be installed in the usual way:

if (!requireNamespace("BiocManager", quietly = TRUE))
  install.packages("BiocManager")

BiocManager::install("GenomicRanges")
BiocManager::install("rtracklayer")

You can run things from Uppmax as well as on your local laptop. If you choose to run examples on Uppmax, the relevant module load calls are:

module load deepTools
module load IGV
module load R_packages

R_packages contains all the mentioned R packages and their dependencies: GenomicRanges, rtracklayer. Be sure to have the corresponding modules loaded (and module load bioinfo-tools before anything) before running them.

Things that can be easily done locally across these tutorials: IGV visualization (download the bigWig files as these are not too large), R figures.

Things that will run better on Uppmax: First part of the Minute tutorial is more computationally demanding. It is still small enough that can be run on a laptop, but it will take a few hours. Some deepTools calls, especially fingerprint plots, are also slow, so it may be better to run on Uppmax.

Note

Computationally demanding steps have been precalculated and resulting plots are shown. Some of them can optionally be run again (such as deepTools computations). In those cases it will be noted within the corresponding section.