Cell Painting Gallery

This page provides a guide to the datasets that are available in the Cell Painting Gallery, hosted by the AWS Registry of Open Data (RODA): https://registry.opendata.aws/cellpainting-gallery

Citation/license

All the data is released with CC0 1.0 Universal (CC0 1.0). Still, professional ethics require that you cite the appropriate resources/publications, listed below, when using individual datasets. For example,

We used the dataset cpg0000 (Chandrasekaran et al., 2022a), available from the Cell Painting Gallery on the Registry of Open Data on AWS (https://registry.opendata.aws/cellpainting-gallery/).

Available datasets

All datasets are generated using the Cell Painting assay unless indicated otherwise. Several updates to that protocol exist (Cell Painting wiki).

The datasets are stored with the prefix indicated by the dataset name. E.g. the first dataset is located at s3://cellpainting-gallery/cpg0000-jump-pilot and can be listed using aws s3 ls --no-sign-request s3://cellpainting-gallery/cpg0000-jump-pilot/ (note the / at the end).

The datasets' accession numbers are the first seven characters of the dataset name. E.g. the accession number of the first dataset is cpg0000.

Dataset name	Description	Publication to cite	IDR accession number
cpg0000-jump-pilot	300+ compounds and 160+ genes (CRISPR knockout and overexpression) profiled in A549 and U2OS cells, at two timepoints	3
cpg0001-cellpainting-protocol	300+ compounds profiled in U2OS cells using several different modifications of the Cell Painting protocol	6
cpg0002-jump-scope	300+ compounds profiled in U2OS using different microscopes and settings	7
cpg0003-rosetta	28,000+ genes and compounds profiled in Cell Painting and L1000 gene expression	5
cpg0004-lincs	1,571 compounds across 6 doses in A549 cells	4	idr0125
cpg0012-wawer-bioactivecompoundprofiling	30,000 compound dataset in U2OS cells	1,2	idr0016
cpg0015-heterogeneity	2,200+ compounds and 200+ genes profiles in U2OS cells	8	idr0016,idr0036, idr0033
cpg0016-jump	116,000+ compounds and 16+ genes (CRISPR knockout and overexpression) profiled in U2OS cells	9
cpg0019-moshkov-deepprofiler	8.3 million single cells from 232 plates, across 488 treatments from 5 public datasets, used for learning representations	10

Downloading from Cell Painting Gallery

See Folder Structure for a complete description of data organization in Cell Painting gallery. Note that for each dataset you can download just images, just extracted features and metadata, or both. Note also that many datasets contain separate batches and you may want a subset of available batches.

If you'd like to just browse the data, it's a lot easier to do so using a storage browser.

Publications using datasets in Cell Painting Gallery

	First Author	Title	Year	Publication URL	Dataset Name in Gallery
1	Wawer	Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling	2014	https://doi.org/10.1073/pnas.1410933111	cpg0012-wawer-bioactivecompoundprofiling
2	Bray	A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay	2017	https://doi.org/10.1093/gigascience/giw014	cpg0012-wawer-bioactivecompoundprofiling
3	Chandrasekaran	Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations	2022a	https://doi.org/10.1101/2022.01.05.475090	cpg0000-jump-pilot
4	Way	Morphology and gene expression profiling provide complementary information for mapping cell state	2022	https://doi.org/10.1101/2021.10.21.465335	cpg0004-lincs
5	Haghighi	High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations	2022	https://doi.org/10.1101/2021.09.08.459417	cpg0003-rosetta
6	Cimini	Optimizing the Cell Painting assay for image-based profiling	2022	https://doi.org/10.1101/2022.07.13.499171	cpg0001-cellpainting-protocol
7	Jamali		2022	In Preparation	cpg0002-jump-scope
8	Rohban	Capturing single-cell heterogeneity via data fusion improves image-based profiling	2019	https://doi.org/10.1038/s41467-019-10154-8	cpg0015-heterogeneity
9	Chandrasekaran		2022b	In Preparation	cpg0016-jump
10	Moshkov	Learning representations for image-based profiling of perturbations	2022	https://doi.org/10.1101/2022.08.12.503783	cpg0019-moshkov-deepprofiler

Contributing to Cell Painting Gallery

See Folder Structure for the required folder structure of your data. See Upload for a complete description of how to upload to the Cell Painting gallery bucket.

Any data contributions to Cell Painting Gallery must be accompanied by a pull request to this repository with updates to this README to add your dataset to Available datasets and Publications.

Complementary Datasets

For other sources of publicly available Cell Painting datasets we encourage you to explore:

shntnu / cellpainting-gallery Goto Github PK