structural_DLFA

Deep learning and structure based hypothesis generation for functional annotation

A pipeline for bringing together hypotheses from SAdLSA and AlphaFold to uncover protein structure.

Directories

• database -- contains Database, which is a wrapper for our sqlite3 database
• notebooks -- jupyter notebooks that demonstrate how to use some this software as well as create various visualizations; also some notebooks are for working out various issues.
• output -- CSV output from earlier SAdLSA runs
• parsers -- this package contains modules for parsing Alphafold, SAdLSA, and GenBank data.
• scripts -- scripts for ingesting data into sqlite3 database as well as lookup proteins in Genbank files.
• seq -- data saved from an earlier SAdLSA run
• snippets -- example code from which to crib
• visualizers -- code for visualizing Alphafold and SAdLSA data
• website -- support for our Missouri web site for querying and visualizing sqlite3 data.

Files

• requirements.txt -- python dependencies for database, scripts, and parsers
• Dockerfile -- for building web site container
• docker-compose.yml -- for spinning up the container

Spinning up web site

1. Ensure your environment is setup
   1. docker is installed

      We recommned installing via the website and not via home brew or a linux package manager.

   2. git lfs is installed
   3. you have checked out website/static/dlfa.db via git lfs
2. docker-compose up

   You will see logging messages in your terminal for all GET and POST transactions

3. Surf to https://0.0.0.0:5000

(Yes, eventually the port and host IP will change.)