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01_Installation.md

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Installation

Install and configure conda package manager

Install Miniconda (optional)

We recommend using conda to install TELR and its software dependencies. If your system doesn't have conda installed, please use the following steps to install Miniconda (Python 3.X).

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O $HOME//miniconda.sh
bash ~/miniconda.sh -b -p $HOME/miniconda # silent mode
echo "export PATH=\$PATH:\$HOME/miniconda/bin" >> $HOME/.bashrc # add to .bashrc
source $HOME/.bashrc

conda init # this step requires you to close and open a new terminal before it take effect
conda update conda # update conda

Set up conda channels (optional)

TELR is hosted under bioconda channel (https://bioconda.github.io/recipes/telr/README.html). After installing conda you will need to add the bioconda channel as well as the other channels bioconda depends on. You can skip this step if you already have conda installed and bioconda channel configured.

conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge

Install mamba (optional)

Mamba is a reimplementation of the conda package manager in C++. There is significant speed improvement on TELR installation using mamba versus conda. Please use following command to install mamba into the base conda environment. You can skip this step if you already have mamba installed.

conda install mamba -n base -c conda-forge

For more on mamba: see Mamba's documentation.

Install TELR

We recommend using mamba to install TELR and all its software dependencies in a new conda environment. Note: installation using this way can lead to variable dependency versions.

mamba create -n TELR --channel bioconda telr

Alternatively, TELR and all its software dependencies can be installed directly using the TELR git repository. Note: installation using this approach ensures fixed dependency versions.

git clone git@github.com:bergmanlab/TELR.git
cd TELR
mamba env create -f envs/telr.yml
conda activate TELR
pip install .

Activate TELR Conda Environment

The TELR conda environment must always be activated prior to running TELR. This step adds TELR and its dependencies installed in the TELR conda environment to the environment PATH.

conda activate TELR

NOTE: Sometimes activating conda environments does not work via conda activate env when run through a script submitted to a queueing system, this can be fixed by activating the environment in the script as shown below.

CONDA_BASE=$(conda info --base)
source ${CONDA_BASE}/etc/profile.d/conda.sh
conda activate TELR

For more on Conda: see the Conda User Guide.

Run TELR on test dataset

A test dataset is provided in the test/ directory, you can test whether your TELR installation is successful by cloning TELR repository and running TELR on the test dataset within the local TELR repository. The test run should generally take less than one minute to finish.

git clone git@github.com:bergmanlab/TELR.git
cd TELR/test
conda activate TELR
telr -o test_output -i reads.fasta -r ref_38kb.fasta -l library.fasta