Exploring Python Bioinformatics Packages with Jupyter Notebook#

Shirley Li, Bioinformatician, TTS Research Technology xue.li37@tufts.edu

Date: 2025-10-03

In this tutorial, we will use the Anndata package as an example to show how to run interactive Python sessions through the Tufts Open OnDemand Jupyter App. The example is based on the upgraded cluster and the new OOD environment. For more details, see the 2025 cluster upgrade

Prerequisite#

Familiarity with Linux commands
Experience working with conda environments

Creating conda environment#

Start an interactive job session srun -p batch -n 1 --time=04:00:00 --mem 4g --pty bash
Load anacoda or minoconda module module load anaconda/2025.06.0
Load conda-env-mod module module load conda-env-mod/default
Configure your conda

NOTE (steps in this session only needs to be executed ONCE)

Since your home directory has limited storage, it’s recommended to install conda packages in your group research storage space. Follow these steps:

Create two directories in your group research storage space (one for storing the envs, one for storing the pkgs, for example: condaenv, condapkg)

$ mkdir /cluster/tufts/XXXXlab/$USER/condaenv/

$ mkdir /cluster/tufts/XXXXlab/$USER/condapkg/

If you haven’t used conda before on the cluster, create a file named “.condarc” in your home directory.

Now add the following 4 lines to the .condarc file in your home directory (modify according to your real path to the directories):
```
envs_dirs:
  - /cluster/tufts/XXXXlab/$USER/condaenv/
pkgs_dirs:
  - /cluster/tufts/XXXXlab/$USER/condapkg/
```
After this, your .condarc file should look like this

$ cat ~/.condarc
```
envs_dirs:
  - /cluster/tufts/XXXXlab/$USER/condaenv/
pkgs_dirs:
  - /cluster/tufts/XXXXlab/$USER/condapkg/
channels:
  - bioconda
  - conda-forge
  - defaults
```

Create your conda environment with conda-env-mod

Change yourenvname to the name of the environment you intend to create

cd /cluster/tufts/XXXXlab/$USER/condaenv/
conda-env-mod create -p yourenvname python=3.8  --jupyter

Accept Terms of Service (ToS) if there is any. You will see something like this, and enter y to continue

The following NEW packages will be INSTALLED:

  _libgcc_mutex      conda-forge/linux-64::_libgcc_mutex-0.1-conda_forge
  _openmp_mutex      conda-forge/linux-64::_openmp_mutex-4.5-2_gnu
  asttokens          conda-forge/noarch::asttokens-2.4.1-pyhd8ed1ab_0
  bzip2              conda-forge/linux-64::bzip2-1.0.8-hd590300_5
  ca-certificates    conda-forge/linux-64::ca-certificates-2024.7.4-hbcca054_0
  ...

Proceed ([y]/n)? y

When it’s complete, you will see something like this.

Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done
+---------------------------------------------------------------+
| To use this environment, load the following modules:          |
|     module load use.own                                       |
|     module load conda-env/project_merfish-py3.13.5            |
| (then standard 'conda install' / 'pip install' / run scripts) |
+---------------------------------------------------------------+
Jupyter kernel created: "Python (My project_merfish Kernel)"
+---------------------------------------------------------------+
| We recommend installing packages into your kernel environment |
| via the command line (with 'conda install' or 'pip install'). |
+---------------------------------------------------------------+
Your environment "project_merfish" was created successfully.

Activate conda environment and install new packages

Note: conda-env/project_merfish-py3.11.5 this may be different and it depends on what yourenvname you have

module load use.own
module load conda-env/project_merfish-py3.11.5

conda list # check packages installed in this environment

pip install jupyter
pip install anndata

conda list # check again

# packages in environment at project_merfish:
#
# Name                     Version          Build               Channel
_libgcc_mutex              0.1              conda_forge         conda-forge
_openmp_mutex              4.5              2_gnu               conda-forge
_python_abi3_support       1.0              hd8ed1ab_2          conda-forge
asttokens                  3.0.0            pyhd8ed1ab_1        conda-forge
bzip2                      1.0.8            hda65f42_8          conda-forge
ca-certificates            2025.8.3         hbd8a1cb_0          conda-forge
comm                       0.2.3            pyhe01879c_0        conda-forge
cpython                    3.13.7           py313hd8ed1ab_100   conda-forge
debugpy                    1.8.17           py313h5d5ffb9_0     conda-forge
...

Create a jupyter kernel

conda-env-mod kernel -n project_merfish

You will see something like this:

requested kernel with arguments:  -n 'project_merfish' --
Jupyter kernel created: "Python (My project_merfish Kernel)"
+---------------------------------------------------------------+
| We recommend installing packages into your kernel environment |
| via the command line (with 'conda install' or 'pip install'). |
+---------------------------------------------------------------+

Using Open Ondemand Jupyter Lab#

Natigate to Open Ondemand

In Open Ondemand dashboard, let’s go to Interactive APPs => Jupyter and select the number of hours, number of cores, and Amount of memory that you would like to request and Launch this job.

Under Notebook, select the kernel you just created. Ex: anndata_python.

Start your python code from there.

Example code to check the Anndata installation:

import anndata as ad
from scipy.sparse import csr_matrix
print(ad.__version__)

Tutorials for ANNDATA#

https://anndata.readthedocs.io/en/latest/tutorials/notebooks/getting-started.html

Some basic python commands#

Check current path

import os
print(os.getcwd())

Go to a new path

os.chdir('/cluster/tufts/XXLAB/$USER/')

Check what files exist in current path

os.listdir(os.getcwd())