Presets

Presets let you save a named configuration of pipeline parameters so you can reuse them across multiple jobs without re-entering values each time.

What presets save

A preset saves all form values for a given pipeline — for example, for the FASTQ pipeline:

• Chain Type
• AIRR Mode
• Species
• Any optional parameters you configured

Presets do not save input files (those must be uploaded per job).

Creating a preset

Navigate to Manage Presets

1. Enter a preset name
2. Fill in the parameter form
3. Click Save Preset

Using a preset

• When creating a new job, user could see all saved templates. Click Apply Preset from any of the saved templates. Select a preset to populate the form with its saved values.
• Another way is to select Manage Presets from the job management page of a pipeline. Select the Action button and select Apply.

Tip

You can load a preset and then modify individual fields before submitting. The preset values are just starting values — they don’t lock you in.

Managing presets

Navigate to Manage Presets to see all presets for a pipeline.

From this list you can:

• Apply to use it
• Edit a preset
• Delete a preset
• Duplicate a preset (creates a copy for the ease of editing)

Sample run presets

Some pipelines arrive with a sample run preset you did not create. These are maintained centrally by your administrator and copied into your account so you have a known-good starting configuration — several also come with a downloadable sample input file, so you can submit a complete run without supplying your own data first.

Your copy is a normal preset: edit it, duplicate it, or delete it freely. Editing your copy never affects anyone else’s.

Note

An administrator can push a sample run out to existing accounts. A preset you already hold under that name is left untouched, so your edits are never overwritten — but if you renamed your copy, the push will land alongside it as a second preset.

Preset scope

Presets are per-user and per-pipeline — a preset you create is visible only to you, and only on the pipeline it was saved for. The one exception is the sample runs described above, which start as a shared master copy before being cloned into each account.