2  Install and prepare the demo

2.1 System requirements

These instructions use the public repository and its demo configuration. An institutional checkout may supply different input paths, a different output folder, and cluster controllers. Use its local setup instructions before running the demo commands.

  • Linux with git and curl, plus HTTPS access to GitHub, Pixi, and 10x Genomics downloads.
  • At least 60 GB of RAM. This is enough for one heavy target at a time; machines near the minimum should reduce concurrent workers in crew_controllers.R.
  • At least 30 GB of free disk space for the public inputs, pixi environment, temporary files, and approximately 6 GB of demo outputs.
  • Multiple CPU cores are strongly recommended. The timing quoted in the next chapter was measured with 16 logical threads.

The committed crew_controllers.R provides a local setup for a 16-CPU, 256-GB workstation and can run several workers concurrently. Review Distributed computing before running on a smaller machine or a scheduler.

2.2 Set up the demo

Run this block from the directory where you want to clone multiomeR. The single pixi run setup command installs the locked environment before its setup-demo task downloads the two configured public inputs and installs the pinned GitHub-only R packages.

Bash
# Clone the repository and enter its root directory.
git clone https://github.com/koefoeden/multiomeR.git
cd multiomeR

# Skip these two lines when pixi is already available on PATH.
curl -fsSL https://pixi.sh/install.sh | sh
export PATH="$HOME/.pixi/bin:$PATH"

# Install the locked environment, download 3.9 GB of demo inputs, and install
# the pinned GitHub versions of BPCells, Signac, and betterChromVAR.
pixi run --use-environment-activation-cache --locked --run-post-link-scripts setup-demo

# Start R in the configured environment for the commands in the next chapter.
pixi run --use-environment-activation-cache --locked R

The download task is restart-safe: non-empty files already present under example_data are skipped. The repository includes the small reference.json from the exact refdata-cellranger-arc-GRCh38-2020-A-2.0.0 reference used for both public outputs, so the full Cell Ranger ARC reference is not required.

Continue to Run the demo from the R prompt.