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LINCS Cell Painting profile data repository

DOI

The Library of Integrated Network-Based Cellular Signatures (LINCS) Project aims to create publicly available resources to characterize how cells respond to perturbation. This repository stores Cell Painting readouts and associated data-processing pipelines for the LINCS Cell Painting dataset.

In this project, the Connectivity Map team perturbed A549 cells with 1,571 compounds across 6 doses in 5 technical replicates. The data represent a subset of the Broad Drug Repurposing Hub collection of compounds.

We refer to this dataset as LINCS Pilot 1. We also include data for the second batch of LINCS Cell Painting data, which we refer to as LKCP.

For a specific list of compounds tested, see metadata. You can interactively explore information about the compounds in the CLUE Repurposing app.

The Morphology Connectivity Hub is the primary source of this dataset.

Image-based profiling

We apply a unified, image-based profiling pipeline to all 136 384-well plates from LINCS Pilot 1, and all 135 384-well plates from LKCP. We use pycytominer as the primary tool for image-based profiling.

We process and store level 3 to level 5 profiles in the profiles/ directory. Furthermore, spherized and conensus profiles can be found in their relevant folders.

See profiles/README.md for more details and for instructions on how to reproduce the pipeline. For further details about image-based profiling in general, please refer to Caicedo et al. 2017.

Computational environment

We use conda to manage the computational environment.

To install conda see instructions.

We recommend installing conda by downloading and executing the .sh file and accepting defaults.

After installing conda, execute the following to install and navigate to the environment:

# First, install the `lincs` conda environment
conda env create --force --file environment.yml

# If you had already installed this environment and now want to update it
conda env update --file environment.yml --prune

# Then, activate the environment and you're all set!
conda activate lincs

Also note that when contributing to the repository, make sure to add any new package in the environment.yml file.

License

We use a dual license in this repository. We license the source code as BSD 3-Clause, and license the data, results, and figures as CC0 1.0.

Citation

If you use these data or software, please cite our Zenodo archive:

Natoli, Ted, Way, Gregory, Lu, Xiaodong, Logan, David, Alimova, Maria, Hartland, Kate, Golub, Todd, Carpenter, Anne, Singh, Shantanu, Subramanian, Aravind. (2021). broadinstitute/lincs-cell-painting: Full release of LINCS Cell Painting dataset (Version v1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.5008187