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Installation

These instructions assume that you have installed MinKNOW and are able to run it.

Install from conda

We also assume that you are using conda -- See instructions here to install conda on your machine.

Step 1: Create a new conda environment or install nodejs into your current conda environment

Create a new conda environment and activate it via:

conda create -n artic-rampart -y nodejs=12 # any version >10 should be fine
conda activate artic-rampart

Or install NodeJS into your currently activated environment via:

conda install -y nodejs=12 # any version >10 should be fine

Step 2: Install RAMPART

conda install -y artic-network::rampart

...this will install the latest release. To install a particular version (say, 1.1.0) use:

conda install -y artic-network::rampart=1.1.0

Step 3: Install dependencies

Note that you may already have some or all of these in your environment, in which case they can be skipped. Additionally, some are only needed for certain analyses and can also be skipped as desired.

If you are installing RAMPART into the artic-ncov2019 conda environment, you will already have all of these dependencies.

Python, biopython, snakemake and minimap2 are required

conda install -y "python>=3.6"
conda install -y anaconda::biopython 
conda install -y -c conda-forge -c bioconda "snakemake-minimal=5.8.1" # later snakemake versions will not work currently
conda install -y bioconda::minimap2=2.17

If you are using MinKNOW to separate samples by barcodes, you don't need Porechop, however if you require RAMPART to perform demuxing then you must install the ARTIC fork of Porechop:

python -m pip install git+https://github.com/artic-network/[email protected]

If you wish to use the post-processing functionality available in RAMPART to bin reads, then you'll need binlorry:

python -m pip install binlorry==1.3.0_alpha1

Step 4: Check that it works

rampart --help

Install from source

(1) Clone the Github repo

git clone https://github.com/artic-network/rampart.git
cd rampart

(2) Create an activate the conda environment with the required dependencies. You can either follow steps 1 & 3 above, or use the provided environment.yml file via

conda env create -f environment.yml
conda activate artic-rampart

(3) Install dependencies using npm

npm install

(4) Build the RAMPART client bundle

npm run build

(5) (optional, but recommended) install rampart globally within the conda environment so that it is available via the rampart command

npm install --global .

Check that things work by running rampart --help