Content Comparison

Step 1 - Search

Multiqc

Go to anaconda.org and search for multiqc in the search bar:

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The “conda install” on the above page gives the installation commands:

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The conda part in the red circle needs to be changed to mamba, and the bioconda part in the blue box is the channel name of this multiqc package. Channel is similar to the name of an online folder, that mamba can find and download the correct package. This is important for the next step.

The command given here CANNOT be directly used on ASU supercomputers, the sections below will show you how to re-write an install command.

Step 2 - Install

1. Connect to the VPN

2. Open a command line interface on Sol by navigating to sol.asu.edu on your browser and
   selecting the "Sol Shell Access" option from the "System" menu option. Or by SSHing into
   Sol using the command ssh <asurite>@sol.asu.edu

3. interactive -p htc -c 4 -t 30

4. module load mamba/latest

5. If the package is for running codes on GPUs, a compatible cuda module is also needed.

6. Now we are ready to create env and install packages. It can be done in separated commands, but the fastest way is to do it in a single command, here is how:

   1. Create an environment:

      Code Block
      mamba create -n myENV -c conda-forge python=3 source activate myENV

   2. Install Multiqc using the command found in step 1

      Code Block
      mamba install -c bioconda multiqc

   3. Combine commands from a, b, c into the fastest single command:

      Code Block
      mamba create -n myENV -c conda-forge -c bioconda python=3 multiqc

7. And answer Y to the promoted question, if everything looks fine

8. Wait till the installation finish

The -c flag in the mamba create above command (#6) means “channel". The channel name must be correct to install the correct package. In our case, the channel of multiqc is bioconda, as found in “Step 1 - Search” section. More information can be found here: Managing Python Modules Through the Mamba Environment Manager

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As explained in Python Package Installation Method Comparison , if a package is not found on anaconda.org, but found on pypi.org , pip can be used inside a mamba env. This is the only correct way to use pip on the ASU supercomputers , the only correct way to use pip on the ASU supercomputers at the moment, is to use it inside an activated mamba env.

There are some packages can only be found on pypi.org but not anaconda.org, then the only option to install them is via pip, inside an activated mamba env. Notably that the current official installation guide for both tensorflow and pytorch prefers pip, but the conda-forge channel still supports them, and our public tensorflow/pytorch environments were built via mamba.

Here is an example of such a special we take a python package called q2-greengenes2:

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as an example. The commands to have this package it installed via pip to a mamba env are:

1. Connect to the VPN

2. Open a command line interface on Sol by navigating to sol.asu.edu on your browser and
   selecting the "Sol Shell Access" option from the "System" menu option. Or by SSHing into
   Sol using the command ssh <asurite>@sol.asu.edu

3. interactive -p htc -c 4 -t 30

4. module load mamba/latest

5. Two options here

   1. If you have an existing env: source activate myENV

   2. If you want to build a new env:

      Code Block
      mamba create -n myENV -c conda-forge python=3 source activate myENV

6. pip install q2-greengenes2

Step 5 - Jupyter Notebook

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