Tutorial: running raccoon-nf

Tutorial: running raccoon-nf#

This tutorial walks through the complete workflow lifecycle in GLACIER — adding a workflow repository, installing it, examining its parameters, and launching a test run — using the raccoon-nf pipeline as an example.

Step 1: Add the workflow repository#

Start from the Library page. If you have not added any catalogues yet, the page will be empty.

  1. Click the Actions button in the top-left corner.

  2. Select Add Repository.

  3. Fill in the dialog:

    • Name: raccoon-nf

    • Repository URL: https://github.com/artic-network/raccoon-nf

    • Version: latest

  4. Click Add.

GLACIER creates a User collection catalogue entry and adds a workflow card for raccoon-nf to the Library.

Step 2: Install the workflow#

The new raccoon-nf card shows an Install button. Click it.

GLACIER clones the repository from GitHub into your workflows directory. The button label changes to Launch once the clone completes.

Step 3: Explore the parameters#

Click the raccoon-nf card to open the Parameters page. Three tabs are available:

  • Info — renders the workflow’s README.md.

  • License — shows the LICENSE file.

  • Params — the configuration form generated from nextflow_schema.json.

Switch to the Params tab. You will see several collapsible sections:

Section

Purpose

Input Options

Input FASTA file, metadata, sequence ID settings.

Pipeline Options

Alignment-only mode, masking, tree model, outgroup, threads.

Sequence QC Options

Minimum length, max N content, header templates.

Alignment QC Options

SNP flagging thresholds, clustering settings.

Tree QC Options

APOBEC/ADAR checks, long branch detection.

Output Options

Output directory name, figure height.

The fasta field under Input Options is marked as required (with a red indicator). It must point to an input FASTA file for a normal run. For this tutorial we will use the Test launch button instead, which provides its own test data.

At the bottom of the page you will see a Profiles dropdown listing the available Nextflow profiles:

  • debug, standard, conda, mamba, docker, arm, singularity, podman, shifter, charliecloud, apptainer, wave, gpu, test

Because the test profile exists, Test launch is available alongside the Launch button.

Step 4: Launch with the test profile#

Click Test launch. GLACIER will:

  1. Select the test profile (combined with standard for Docker support).

  2. Create a new instance with an auto-generated name (e.g. brave-lion).

  3. Launch the pipeline using the bundled Nextflow and test data defined in conf/test.config.

  4. Navigate to the Monitor page.

The test profile configures a minimal set of inputs:

fasta      = assets/test_data
metadata   = assets/test_data
min_length = 2000
tree_model = HKY+G

These are small files bundled in the raccoon-nf repository, so the pipeline completes quickly.

Step 5: Monitor the run#

On the Monitor page, watch the pipeline progress in real time.

Progress tab#

The Progress tab shows a tree of process groups (e.g. RACCOON_NF:SEQ_QC, RACCOON_NF:ALIGNMENT). Each process node has status icons (pending / submitted / completed / error) and a progress bar for multi-task processes.

Click the ⋮ menu on any completed process to inspect its log files — .command.out, .command.err, .command.sh, and more.

Logs tab#

Switch to the Logs tab for live-updating streams:

  • stdout — Nextflow’s standard output (refreshes every 1 second).

  • stderr — Nextflow’s standard error.

  • nextflow.log — Nextflow’s internal log file.

Reports tab#

When the pipeline finishes, the Reports tab may contain HTML output files generated by raccoon-nf (e.g. pipeline reports, tree visualisations).

Run controls#

Use the header buttons while the pipeline is running:

Button

Action

Cancel

Graceful stop (SIGINT).

Kill

Force stop (SIGKILL).

Resume

Re-launch with -resume from the last checkpoint.

Open Results Folder

Open the instance directory in your file manager.

Step 6: View the completed instance#

Switch to the Instances page (sidebar storage icon). The completed raccoon-nf run appears in the table with a green status icon. Click the icon to re-open the Monitor page and review outputs.

You can inspect the instance directory on disk at:

<documentsPath>/instances/artic-network/raccoon-nf@latest/<instance_name>/

This contains params.json, stdout.log, stderr.log, nextflow.log, the work/ directory, and any reports.

Summary#

In this tutorial you:

  1. Added a workflow repository via Actions → Add Repository.

  2. Installed the workflow by clicking Install.

  3. Explored the parameter form generated from nextflow_schema.json.

  4. Launched the pipeline with Test launch using the test profile.

  5. Monitored progress, logs, and reports on the Monitor page.

  6. Located the completed instance in the Instances page and on disk.

Contents