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: ```bash # 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: ```bash cd backend cargo build --release ``` Building for development: ```bash cd backend cargo build cd ../frontend npm install npm run build ``` ## Run (for developers) Prerequisites: ```bash # 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: ```bash cd backend cargo run --release ``` Running for development: ```bash cd backend cargo run cd ../frontend npm run build:dev ``` ## Testing Backend testing: ```bash cd backend cargo test ``` Frontend testing: ```bash cd frontend npm run test:unit ```