brc-analytics

Setup

Using Node.js version 20.10.0, run npm install in the root directory of the repository to install dependencies.

Using the development server

The app can be run for development using npm run dev, and accessed at http://localhost:3000.

Building the app locally

Run npm run build:local to build. The built app can be run using npm start, and accessed at http://localhost:3000.

BRC Analytics Data Catalog

Building the data source files

Using Python version 3.12.4 is recommended.

Create a Python virtual environment and install requirements:

python3 -m venv ./venv
source ./venv/bin/activate
pip install -r ./catalog/build/py/requirements.txt

Then run the script:

npm run build-files-from-ncbi

The environment can be deactivated by running deactivate, and re-activated by running source ./venv/bin/activate again.

Building the catalog data

To build catalog data for use by the app, run the script:

npm run build-brc-db

Adding new assemblies

The list of assemblies is defined in the YAML file catalog/source/assemblies.yml. Assemblies are labeled with comments specifying the species name (as defined by NCBI), and sorted alphabetically by species.

To add a new assembly, add a new list item to the assemblies entry in the YAML, labeled and sorted as appropriate, consisting of a dictionary with a single entry, accession, specifying the assembly's accession.

For instance, to add a new assembly for Anopheles gambiae with the accession XXX_000000000.0, add this line below the # Anopheles gambiae comment:

- accession: XXX_000000000.0

Updating workflows

Run

npm run iwc-manifest-to-workflows-yaml
npm run build-brc-db

to fetch a list of current workflows from https://iwc.galaxyproject.org/workflow_manifest.json. Only workflows for currently enabled categories are fetched. If necessary, update parameters that require a reference genome id, fasta or gtf file to include the variable slot, containing one of ASSEMBLY_ID, ASSEMBLY_FASTA_URL, or GENE_MODEL_URL. These values will be substituted with assembly-specific values at runtime.

Editing the LinkML schemas

If the LinkML schemas in catalog/schema are edited, the derived JSON schemas and TypeScript definitions should be updated as follows:

1. Ensure that the Python virtual environment is activated, as described above.
2. Run npm run gen-schema.

Overview of automated checks on catalog content

The run-checks GitHub workflow performs checks to ensure that the catalog data and schemas are well-formed; this is done by:

• Linting the schemas via linkml-lint.
• Converting the schemas to Python, to catch any errors that occur.
• Validating the catalog source files against their corresponding schemas.