The ScaleBio Tag Toolkit workflow requires a number of dependencies to run. These include ScaleBio developed and internal executables, python libraries, etc. There are three alternative ways to provide these dependencies; select one of these, depending on what is easiest on your system, and follow the instructions below.
If your system supports docker containers, this is the recommended way to handle all dependencies for the ScaleBio Tag Toolkit workflow. We provide pre-build docker containers and the workflow is setup to automatically use them.
This is enabled by adding -profile docker to the nextflow command-line.
If your system does not support docker, singularity is an alternative that is enabled on many HPC clusters. Setting -profile docker,singularity (no space) will use the singularity engine for all dependencies.
See Nextflow Containers for details and additional configuration options. One important point is that all input and output paths need to be available (bind) inside the containers. For docker, Nextflow should take care of that automatically, for singularity this requires user mounts to be enabled in the system-wide configuration (see the notes in the Nextflow documentation).
Another option is using the Conda package manager to install most dependencies automatically. This is done by setting -profile conda. In this case the following additional steps need to be complete
- Manually Install ScaleBio Tools on your system first.
- If running from a sequencer runFolder (.bcls) Illumina BCL Convert is required to be installed (and available on
$PATH) - In order to run the ArchR analysis step of the pipeline using conda install its dependencies. Alternatively set
--runArchR falseto disable ArchR execution.
A list of all requirements (excluding ArchR dependencies) can be found in envs/scaleAtac.conda.yml and envs/scalereport.conda.yml. This can be used for manual installation in the user environment if required. All tools need to be available on $PATH or based in /path/to/ScaleTagToolkit/bin/