The evolution, evolvability and engineering of gene regulatory DNA

Quickstart

Use the live app now. No downloads. No installation. 👇

Repository overview

The GitHub repository is organized into two directories :

app : A fully self-contained directory for running the interactive application to compute mutational robustness, evolvability vectors and expression.
manuscript_code : The codebase corresponding to the manuscript. The organization of this directory is further described here.

Run the app locally

If you wish to run the app on your local machine or cluster,

Install Docker.
Run the following commands on a terminal :

docker pull edv123456789/evolution_app:latest

docker run --rm -d  -p 8501:8501/tcp edv123456789/evolution_app:latest

The app is now running and you can access it by navigating to http://localhost:8501/ in your web browser. If running on a remote cluster, you may want to expose port 8501 using ngrok.

Using the model directly

After installing docker and pulling the latest image as described in the first two steps above, run the following on a terminal :

docker run -it --rm --entrypoint /bin/bash edv123456789/evolution_app

python

In the python shell, run :

from app_aux import *

model_condition = 'Glu' #or, 'SC_Ura'

model, _ , __ = load_model(model_condition) 

model.summary()

You have now loaded our tensorflow.keras model. You may use this as is for downstream computations as described in the manuscript or adapt it for your application (e.g. transfer learning).

To exit the python shell and the docker container, simply press Ctrl+D twice.

All data and code

All data and code is also available in an interactive, fully functional form as a CodeOcean capsule (just press 'Reproducible Run' on CodeOcean to reproduce results) at :

Gene Expression Prediction DREAM Challenge 2022

For more details, pleae see the DREAM Challenge webpage

Timeline

Registration Open: April 2022
Launch: May 2, 2022
Webinar: May 2, 2022
Leaderboard Submissions for challenge opens: May 16, 2022
Final Submissions for the challenge: July 30 2022
Winners Announced: August 15, 2022
Results presented at TBD
Access challenge data TBD

Reference

The evolution, evolvability and engineering of gene regulatory DNA, Nature 2022.

Eeshit Dhaval Vaishnav^*§, Carl G. de Boer^*§, Jennifer Molinet, Moran Yassour, Lin Fan, Xian Adiconis, Dawn A. Thompson, Joshua Z. Levin, Francisco A. Cubillos, Aviv Regev^§.

DOI : https://doi.org/10.1038/s41586-022-04506-6

1edv/evolution