Installation¶
The easiest way to install is through conda, which will also install the dependencies:
conda install poppunk
Then run with poppunk.
Important
From v2.1.0 onwards, PopPUNK requires python3.8 to run
(which on many default Linux installations is
run using python3 rather than python).
Important
From v2.1.2 onwards, PopPUNK no longer supports mash. If you want to
use older databases created with mash, please downgrade to <v2
Installing with conda (recommended)¶
If you do not have conda you can install it through
miniconda and then add the necessary
channels:
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
Then run:
conda install poppunk
If you are having conflict issues with conda, our advice would be:
- Remove and reinstall miniconda.
- Never install anything in the base environment
- Create a new environment for PopPUNK with
conda create -n pp_env poppunk
If you have an older version of PopPUNK, you can upgrade using this method – you
may also wish to specify the version, for example conda install poppunk==2.3.0 if you
wish to upgrade.
conda-forge also has some helpful tips: https://conda-forge.org/docs/user/tipsandtricks.html
Installing with pip¶
If you do not have conda, you can also install through pip:
python3 -m pip install poppunk
This may not deal with all necessary Dependencies.
Clone the code¶
You can also clone the github to run the latest version, which is executed by:
git clone https://github.com/johnlees/PopPUNK.git && cd PopPUNK
python3 poppunk-runner.py
This will also give access to the Scripts.
You will need to install the Dependencies yourself (you can still use conda or pip for this purpose).
Dependencies¶
This documentation refers to a conda installation with the following packages:
- python3 (3.8.2)
pp-sketchlib(1.6.2)DendroPy(4.3.0)hdbscan(0.8.13)matplotlib(2.1.2)graph-tool(2.31)numpy(1.14.1)pandas(0.22.0)scikit-learn(0.19.1)scipy(1.0.0)sharedmem(0.3.5)
Optionally, you can use rapidnj
if producing output with --microreact and --rapidnj options. We used
v2.3.2.