This repo holds the content I wrote for a mini workshop to teach a group of graduate students, consisting mostly of biologists with very little exposure to programming, how to code. They needed programming to analyse datasets that vary from DNA sequences, typical statistical data, and some basic language processing. The initial feedback from the students was: "We don't know where to begin". So, in this tutorial my goal was to make them comfortable with basic programming idioms, and a very short primer on how to use libraries (mostly the standard library) to do more complex tasks.
To go through the content, just click on the "launch binder" button, which should take you to mybinder.org. Initially you might need to wait a while for the image to be created. Once done, and a jupyter server is running, you may click on the notebook concepts.ipynb and explore away.
While writing the tutorial, I versioned the notebook by syncing it
with a python file using jupytext. You may use the
Makefile to generate the notebook from the python file (or vice
versa). If you work on the notebook directly, you could sync it with
the python file using the jupyter integration provided by
jupytext. I have used the light syntax. I use RISE to present the notebook as
interactive slides during the tutorial.
Note: possibly due to a bug in the Jupyter integration of
jupytext, I could not sync my configurations for RISE to the
python file. Since this was one line, I simply fixed this manually.
I have a small helper library under tutorial. So that imports
work without fiddling with sys.path, it is advised to do the
exercises and run the notebook from the top-level directory.
I have also included a few small datasets under data. They are:
example.fa : a fasta file from this Kaggle kernel,
human_ancestor_Y.fa.bz2 : a compressed fasta file for the Y chromosome from the 1000 Genome Project (1KGP),
summary.txt : a TSV file summarising the above dataset from the 1KGP.
python*.png : The image files are from <https://www.python.org/>.
The lesson and exercises uses the standard library, except for the
part where I discuss data analysis libraries like numpy,
pandas. To present the notebook, RISE is required. To
sync/generate the notebook jupytext is required.
Hope this is useful to people out there 😇.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.