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This is the future

Conda on Marvin on a per user basis, so you have total control over it. Log in and from the command line type Only ever do this once or you will get error pessages):


Either log out and back in, or type:

source ~/.bashrc

This will make a user specific version of conda avaible to you.

To find the package you want, search here:

or google search: - as there are multiple channels!!

conda name_of_tool_you_want

We strongly advise using environments: You can do this in many ways. Please see the link for more details (here you can specifiy exact version etc ..) 

The easiest usage would be: e.g.


This is an example of a toold called roary

conda create -n roaryENV roary

once it has installed, you can activate the environment by typing:

conda activate roaryENV

As a lot of tools have dependencies, all the dependencies should be installed during this process. It is a good idea to keep them looked up in their own ENV, so they dont interfere with dependencies and spcific version required for other things you have installed.

To get the latest version

conda update roary

You are now ready to use this package.

conda deactivate        to leave this environment.

If you want to install a specific version of a tool (use the equals sign and the version you want):

conda create -n samtools1.3 samtools=1.3


conda create -n python27 python=27

once you have this version of python installed, you can easily use (after you have activated the python env:

pip install biopython   (or whatever you require)

conda and perl Firstly, perl is a pain to look after. The way the cluster has been historically set up, all perl versions and modules are different on all the nodes. The new cluster will not be like this. Therefore, we cannot install modules for every user on all the nodes. What we recommend is you having you own perl version using conda:

conda create -n perlEnv perl
conda activate perlEnv

then install the modules you want
cpan App::cpanminus

cpanm Term::ReadKey

Bioperl is difficult to install. Fact. But someone has put this in coda. So lets use that:

conda create -n bioperlEnv perl-bioperl

To list all the environments you have created (you will forget the envs after a while, so name them well!!):

conda info –envs

To list all the dependencies you have within an env

conda list -n envname

For example, trinity comes with jellyfish, which can be difficult to install. Therefore some of these tools are a treasure chest of cools tools, which can save many hours and kg of pain in installation process.

To install multiple tools in one env:

conda create -n python36_bioperl python=3.6 perl-bioperl mummer scipy numpy biopython matplotlib

You can activate multiple conda envs, they have preference as the latest is used first in you path:

conda activate trinityenv
conda activate python27
conda activate python36

in this example, a simple python command will use the python3 version as this was the last to be activated, if you want python 2. You have to specifiy python2. The perl will be the one in the monster python36 env i created. But jelly fish will be from the trinity env. Make sense?


installing packages:

conda and samtools problems

Bascially sometimes this get installed from the wrong channel. This may happen with other tools. We havent come across this yet.

The problem will look like this if you try to use samtools:

samtools: error while loading shared libraries: cannot open shared object file: No such file or directory).

The solution:

install from the bioconda channel: -c bioconda 
conda install -c bioconda samtools

or specifically the problem was found with unicycler: remove the old unicycler failed install:

conda remove --name unicyclerENV --all 

remake this env from the bioconda channel:

conda create -n unicyclerENV -c bioconda unicycler

to update the base conda, if required

conda update -n base conda

conda hanging on solving environment

Can you try this please, then try re installing the beastie package.

conda config --remove channels conda-forge
conda config --add channels conda-forge

if this still doesnt work try:

conda config --set channel_priority strict