Tutorials for this package describe how to use the package functions for research with the provided data. All the tutorials are written in Python using the interactive Jupyter notebooks. If you are unfamiliar with Jupyter, follow the instructions given here on the Jupyter website. You will then be able to run our tutorials as interactive, exploratory data analyses.
In general, tutorials are basic coding introduction to the API as well as conventions for storing and accessing the data. The use cases are short examples focused on a biological question and show practical uses of the API for biological discovery.
- Tutorial 1: CPTAC data introduction
- Tutorial 2: Using pandas to work with cptac dataframes
- Tutorial 3: Joining dataframes with cptac
- Tutorial 4: Understanding multi-indexes
- Tutorial 5: How to keep up to date with new package and data releases
- Use Case 1: Comparing transcriptomics and proteomics for a single gene
- Use Case 2: Looking for correlation between clinical attributes
- Use Case 3: Associating clinical variables with omics data