Installation

The following sections describe how to install tRNAnalysis.

Conda Installation

The our preffered method of installation is using conda. If you dont have conda installed then please install conda using miniconda or anaconda.

tRNAnalysis is currently installed using the bioconda channel and the recipe can be found on `github `_.

To install tRNAnalysis:

conda install -c bioconda trnanalysis

Conda environment

Conda is an awesome project, however it can suffer from significant issues relating to how long it takes the solver to fix installation issues. For more information regarding these conda issues please see bioconda issues.

In order to try and speed things up we have provided a conda environment for installation. Currently only linux is supported and it can be installed by doing the following:

wget https://raw.githubusercontent.com/Acribbs/tRNAnalysis/master/conda/environments/trnanalysis-linux.yml
conda env create -f trnanalysis-linux.yml
conda activate trnanalysis-env

Pip installation

We recommend installation through conda because it manages the dependencies. However, tRNAnalysis can also be installed easily using the pip package manager. However, you will also have to install other dependencies manually:

pip install trnanalysis

Manual installation

To obtain the latest code, check it out from the public git repository and activate it:

git clone https://github.com/Acribbs/tRNAnalysis.git
cd tRNAnalysis
python setup.py install

Once checked-out, you can get the latest changes via pulling:

git pull origin master

Installing additonal software

When building your own workflows we recomend using conda to install software into your environment where possible.

This can easily be performed by:

conda search <package>
conda install <package>