Protein Function Prediction

A python program that aims to predict protein function prediction using protein-protein interaction networks and go term data.

Setup

• Download conda
• Once you have cloned the repo, do the following command to create a conda environment with the necessary packages:
• conda env create -f environment.yml
• Now you have a conda environment that has all the necessary packages for this project
• To test that everything is working, you can run python main.py

Files

• main.py: File used to run the algorithms
• neighbor_accuracy: Computes how accurately the neighbors of a GO term can be predicted using random walk
• accuracy_stats.py: Computes stats on neighbor_accuracy
• difference.py: Takes two matched outputs from main and prints a table comparing them
• distribution.py: Visualizes the distribution of GO term neighbor counts
• small_graph.py: Visualizes the impact of pagerank on a directed and undirected graph using a test dataset
• subgraph.py: Visualizes a subgraph of the one built in main based on pagerank node ranks
• paired_sample.py: An additional way to generate pos/neg samples keeping specific aspects constant (then run main with new_random_lists set to False)