rtwalton / opticalpooledscreens Goto Github PK

Code and computational tools related to the preprint publication, The phenotypic landscape of essential human genes.

For new projects using optical pooled screens, it is highly recommended to use the Github repository accompanying our upcoming Optical Pooled Screens protocol paper: https://github.com/feldman4/OpticalPooledScreens.

This repository contains additional application-specific resources for our study of essential gene function using optical pooled screens.

This includes:

• Many additional image features implemented as functions operating on scikit-image RegionProps objects (features come from CellProfiler and additional sources)
• Functions for analyzing live-cell optical pooled screens (calling TrackMate for cell tracking)

WARNING: many versions of dependencies will have trouble installing on Python 3.8. It is currently recommended to use Python 3.6. Setting up a Python 3.6 conda environment may be a convenient solution, set-up guide here.

Download the OpticalPooledScreens directory (e.g., on Github use the green "Clone or download" button, then "Download ZIP").

In Terminal, go to the OpticalPooledScreens project directory and create a Python 3 virtual environment using a command like:

python3 -m venv venv

If the python3 command isn't available, you might need to specify the full path. E.g., if Miniconda is installed in the home directory:

~/miniconda3/bin/python -m venv venv

This creates a virtual environment called venv for project-specific resources. The commands in install.sh add required packages to the virtual environment:

sh install.sh

The ops package is installed with pip install -e, so the source code in the ops/ directory can be modified in place.

Once installed, activate the virtual environment from the project directory:

source venv/bin/activate