MriSequencingPipeline/README.md

Encapsulated Sequencing Pipeline Engine

Design philosophy

This encapsulated sequencing pipeline engine (ESPE) is intended as a simple, streamlined, well documented and tested solution for common sequencing data analysis setups. Since transformation and analysis of sequencing data is typically a time and resource consuming task, the main focus is not placed on scalability of a centralised processing pipeline for e.g. a core facility. Rather an engine is provided to allow easy setup of the pipelines of choice within a specific workgroup. The software itself is self-contained, so all processed data and associated information (database etc.) is stored locally with the software. While this severely limits the scalability it allows for an easy setup, documentation and improves general usability. For the same reasons execution of pipelines themselves is not paralellised. Instead each pipeline step uses paralellisation whenever possible. Additonally, each pipeline step can be configured as desired by the user and runs inside a container to prevent data and package conflicts, allow for running arbitrary pipeline steps without the need to install additional software and mitigate difficulties during setup.

Architecture

Frontend

Vue.js with the Quasar framework is used for easy implementation of the frontend.

Backend

An actix-Rust-backend is used as a statically typed, fast and reliable backend.

Database

SQLite is used as it provides a simple, self-contained and fast database. Diesel is used for automated database migration.

Containerisation

Docker was selected as tool for running and managing containers due to its ease of use and widespread adoption.

Usage

TODO: Create and add link to full user guide.

Enviroment variables

Also see backend/.env.

Variable	Description
CONTEXT_FOLDER	the context folder of the application where all relevant data is stored
DATABASE_URL	the database location
LOG_LEVEL	the minimum log level of the application (debug, info, warn, error)
PIPELINE_FOLDER	the folder storing pipeline definitions
SERVER_ADDRESS	the address of the server
SERVER_PORT	the port of the server

Build (for developers)

Prerequisites:

# Install Rust.
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
# Install Node.
curl -fsSL https://deb.nodesource.com/setup_lts.x | sudo bash -
sudo apt update
sudo apt install nodejs
# Install the requirements for the openssl crate.
sudo apt install libssl-dev

Conventional release build:

cd backend
cargo build --release

Building for development:

cd backend
cargo build
cd ../frontend
npm install
npm run build

Run (for developers)

Prerequisites:

# Install SQLite and the Diesel dependency.
# The version requirement for SQLite is >= 3.35.
sudo apt install sqlite3 libsqlite3-dev
# Install Diesel.
cargo install diesel_cli --no-default-features --features sqlite
# Initialise the database.
cd backend
mkdir application # without the sub-folder Diesel will fail to create the database
diesel setup
# Install docker for containerisation of the pipeline.
sudo apt install docker.io

Running a release build:

cd backend
cargo run --release

Running for development:

cd backend
cargo run
cd ../frontend
npm run build:dev

Testing

Backend testing:

cd backend
cargo test

Frontend testing:

cd frontend
npm run test:unit