Programmatic access to MGnify resources with APIs and notebooks: practical

Trainer: Sandy Rogers

Overview:  The practical will be completed by following an interactive Jupyter Notebook (including modifying and writing some pieces of Python code). Experience with the Python data analysis ecosystem (e.g. Pandas and Matplotlib) will be helpful, but solutions will be included too.

Materials:

• Practical

Learning outcomes

After this session you should be able to:

• Identify the role that Metagenome-Assembled Genomes (MAGs) play within MGnify
• Identify MAG catalogues and explore their annotations
• Access data on MGnify

Background materials:

• MGnify web site
• MGnify MAG catalogue article
• “Python Data Science Handbook” (uses Jupyter Notebooks to introduce Pythonic data science); chapters 3 and 4 cover Pandas and Matplotlib
• “ultraquick” tutorial for Pandas using a Jupyter Notebook by Google