# Complete Datasets

| Dataset name | Description | Publication to cite | Associated repositories | Total size | Images size | Numerical data size | Cell Painting protocol | Other aliases |
| -- | -- | -- | -- | :--: | :--: | :--: | :--: | :--: |
| cpg0000-jump-pilot | 300+ compounds and 160+ genes (CRISPR knockout and overexpression) profiled in A549 and U2OS cells, at two timepoints | (Chandrasekaran et al., 2024) [Publication](https://doi.org/10.1038/s41592-024-02241-6), [Preprint](https://doi.org/10.1101/2022.01.05.475090), Description of Cell Painting v2.5. | [data](https://github.com/jump-cellpainting/2023_Chandrasekaran_submitted), [JUMP Hub](https://broad.io/jump), [JUMP datasets](https://github.com/jump-cellpainting/datasets) | 12.3 TB | 6.1 TB | 6.1 TB | v2.5 | |
| cpg0001-cellpainting-protocol | 300+ compounds profiled in U2OS cells using several different modifications of the Cell Painting protocol | (Cimini et al., 2023) [Publication](https://doi.org/10.1038/s41596-023-00840-9), [Preprint](https://doi.org/10.1101/2022.07.13.499171) Description of Cell Painting v3. | [data](https://github.com/carpenter-singh-lab/2023_Cimini_NatureProtocols), [JUMP Hub](https://broad.io/jump), [JUMP datasets](https://github.com/jump-cellpainting/datasets) | 40.3 TB | 18.7 TB | 21.6 TB | v3 and experiments | |
| cpg0002-jump-scope | 90 compounds (JUMP-MOA plate) profiled in U2OS using different microscopes and settings | (Tromans-Coia and Jamali et al., 2023) [Publication](https://doi.org/10.1002/cyto.a.24786), [Preprint](https://doi.org/10.1101/2023.02.15.528711) | [data](https://github.com/jump-cellpainting/jump-scope), [analysis](https://github.com/jump-cellpainting/jump-scope-analysis), [JUMP Hub](https://broad.io/jump), [JUMP datasets](https://github.com/jump-cellpainting/datasets) | 16.7 TB | 12.5 TB | 4.2 TB | v2.5 | |
| cpg0003-rosetta | 28,000+ genes and compounds profiled in Cell Painting and [L1000](https://doi.org/10.1016%2Fj.cell.2017.10.049) gene expression | (Haghighi et al., 2022) [Publication](https://doi.org/10.1038/s41592-022-01667-0), [Preprint](https://doi.org/10.1101/2021.09.08.459417), | [data](https://github.com/carpenter-singh-lab/2022_Haghighi_NatureMethods) | 8.5 GB | 0 | 8.5 GB | | |
| cpg0004-lincs | 1,571 compounds across 6 doses in A549 cells | (Way et al., 2022) [Publication](https://doi.org/10.1016/j.cels.2022.10.001), [Preprint](https://doi.org/10.1101/2021.10.21.465335) | [data](https://github.com/broadinstitute/lincs-cell-painting) | 65.7 TB | 61.9 TB | 3.8 TB | v2 | idr0125 |
| cpg0005-gerry-bioactivity | 30 related synthetic compounds across 6 doses in U2OS cells | (Gerry et al., 2016) [Publication](https://doi.org/10.1021/jacs.6b04614) | | 356 GB | 356 GB | 200 MB | v1 | |
| cpg0010-caie-drugresponse | MCF-7 breast cancer cells treated  with 113 small molecules at eight concentrations. | (Caie et al., 2010) [Publication](https://doi.org/10.1158/1535-7163.MCT-09-1148) | | 239.2 GB | 98.4 GB | 140.8 GB | other variation | [BBBC021](https://bbbc.broadinstitute.org/BBBC021) |
| cpg0011-lipocyteprofiler | Variety of lipocytes in different metabolic states and with genetic and drug perturbations | (Laber and Strobel et al., 2023) [Publication](https://doi.org/10.1016/j.xgen.2023.100346), [Preprint](https://www.biorxiv.org/content/10.1101/2021.07.17.452050v1) Description of Cell Painting lipocyte variant. | [Batch1 and Batch3 data](https://github.com/broadinstitute/2018_04_12_T2D_V2F_Saadat_Broad), [analysis](https://github.com/ClaussnitzerLab/Lipocyte-Profiler) | 1.2 TB | 1.2 TB | 16 MB | lipocyte | |
| cpg0012-wawer-bioactivecompoundprofiling | 30,000 compound dataset in U2OS cells. Original images re-profiled in 2023 (original profiles available in workspace/gigascience_profiles) | (Wawer et al., 2014) [Publication](https://doi.org/10.1073/pnas.1410933111) Description of Cell Painting v1, (Bray et al., 2017) [Publication](https://doi.org/10.1093/gigascience/giw014) Description of Cell Painting v2 | [data](https://github.com/broadinstitute/2015_Bray_GigaScience-data) | 10.7 TB | 3.1 TB | 7.6 TB | v1 | [idr0016](https://idr.openmicroscopy.org/webclient/?show=screen-1251), CDRP, [BBBC036](https://bbbc.broadinstitute.org/BBBC036), [BBBC047](https://bbbc.broadinstitute.org/BBBC047) |
| cpg0015-heterogeneity | 2,200+ compounds and 200+ genes profiles in U2OS cells | (Rohban et al., 2019) [Publication](https://doi.org/10.1038/s41467-019-10154-8) | [data](https://github.com/carpenterlab/2018_Rohban_NatComm) | 204 GB | 0 | 204 GB | | [idr0016](https://bbbc.broadinstitute.org/BBBC036), [idr0036](https://idr.openmicroscopy.org/webclient/?show=screen-1952) |
| cpg0016-jump | 116,000+ compounds and 15,000+ genes (CRISPR knockout and overexpression) profiled in U2OS cells. Over 8 million images (>126 TB), over 1.5 billion cells of numerical data (>126TB), for over 250 TB data in total. | (Chandrasekaran et al., 2023) [Preprint](https://doi.org/10.1101/2023.03.23.534023) | [JUMP Hub](https://broad.io/jump), [JUMP datasets](https://github.com/jump-cellpainting/datasets) | 358.4 TB | | | v3 | |
| cpg0017-rohban-pathways | 323 genes overexpressed in U2OS cells. Original images re-profiled in 2023 (original profiles not in gallery) | (Rohban et al, 2017) [Publication](https://doi.org/10.7554/eLife.24060), [Preprint](https://doi.org/10.1101/092403) | [re-profiled data](https://github.com/broadinstitute/cpg0017-rohban-pathways), [original data](https://github.com/carpenterlab/2017_Rohban_eLife) | 321 GB | 189 GB | 132 GB | v1 | [BBBC037](https://bbbc.broadinstitute.org/BBBC037), TA-ORF, [idr0033](https://idr.openmicroscopy.org/webclient/?show=screen-1751) |
| cpg0018-singh-seedseq | U2OS cells treated with each of 315 unique shRNA sequences | (Singh et al. 2013) [Publication](https://doi.org/10.1371/journal.pone.0131370) | | 247.1 GB | 247.1 GB | 0 | | [BBBC025](https://bbbc.broadinstitute.org/BBBC025) |
| cpg0019-moshkov-deepprofiler | 8.3 million single cells from 232 plates, across 488 treatments from 5 public datasets, used for learning representations | (Moshkov et al., 2024) [Publication](https://www.nature.com/articles/s41467-024-45999-1), [Preprint](https://doi.org/10.1101/2022.08.12.503783) | [data](https://github.com/broadinstitute/DeepProfilerExperiments), [software](https://github.com/cytomining/DeepProfiler) | 522 GB | 482 GB | 40 GB | dataset dependent | |
| cpg0021-periscope | 30 million cells with 20,000 single-gene knockouts in pooled format. A549 cells and HeLa cells in two growth media | (Ramezani, Weisbart, Bauman, and Singh et al., 2025) [Preprint](https://doi.org/10.1101/2023.08.06.552164), [Publication](https://doi.org/10.1038/s41592-024-02537-7), Description of Cell Painting pooled variant. Also has data from (Haghighi et al., 2023) [Preprint](http://doi.org/10.48550/arXiv.2306.15898), [Paper](https://www.ijcai.org/proceedings/2023/0531.pdf). | [analysis](https://github.com/broadinstitute/2022_PERISCOPE), [A549 data](https://github.com/broadinstitute/CP186-A549-WG), [HeLa data](https://github.com/broadinstitute/CP257-HeLa-WG), [PLePI](https://github.com/carpenter-singh-lab/2023_Haghighi_IJCAI) | 56.0 TB | 45.0 TB | 11.0 TB | pooled | |
| cpg0022-cmqtl | 297 iPSC lines | (Tegtmeyer et al., 2024) [Publication](https://doi.org/10.1038/s41467-023-44045-w), [Preprint](https://doi.org/10.1101/2023.01.09.522731) | [data](https://github.com/broadinstitute/cmQTL) | 3.7 TB | 2.8 TB | 945 GB | v2.5 | |
| cpg0026-lacoste_haghighi-rare-diseases | Protein localization of 3,448 missense variants in 1,269 genes in HeLa cells | (Lacoste and Haghighi et al., 2024) [Publication](https://doi.org/10.1016/j.cell.2024.09.003), [Preprint](https://doi.org/10.1101/2023.09.05.556368) | [analysis](https://github.com/carpenter-singh-lab/2024_LacosteHaghighi_Cell_Mislocalization) | 11 TB | 9.4 TB | 1.6 TB | Protein of interest, Hoechst, ConA, Mitotracker | |
| cpg0028-kelley-resistance | Bortezomib resistant HCT116 clones | (Kelley et al., 2023) [Publication](https://doi.org/10.7554/eLife.91362) | [data](https://github.com/broadinstitute/profiling-resistance-mechanisms) | 4.1 TB | 1.9 TB | 2.2 TB | | |
| cpg0029-chroma-pilot | Comparison of alternative Cell Painting dyes | (Sivagurunathan et al., 2025) [Publication](https://doi.org/10.1016/j.slasd.2025.100268) | [data](https://github.com/broadinstitute/2022_09_07_New_phenotypic_dye_testing_CDoT_Broad_Analysis) | 1.5 TB | 495 GB | 1 TB | v3 and experiments | |
| cpg0030-gustafsdottir-cellpainting | U2OS cells treated with each of 1600 known bioactive compounds. Description of Cell Painting v1. | (Gustafsdottir et al., 2013) [Publication](https://doi.org/10.1371/journal.pone.0080999) | | 234 GB | 234 GB | .3 GB | v1 | [BBBC022](https://bbbc.broadinstitute.org/BBBC022), [idr0036](https://idr.openmicroscopy.org/webclient/?show=screen-1952) |
| cpg0031-caicedo-cmvip | ORF over-expression of 596 alleles of 53 genes in A549 cells. Original images re-profiled in 2023 (original profiles available in workspace/profiles_orig) | (Caicedo et al., 2023) [Publication](https://www.molbiolcell.org/doi/10.1091/mbc.E21-11-0538), [Preprint](https://doi.org/10.1101/2021.11.18.469171) | [original data](https://github.com/broadinstitute/luad-cell-painting), [re-profiled data](https://github.com/broadinstitute/cpg0031-caicedo-cmvip) | 2.2 TB | 605 GB | 1.6 TB | v1 | BBBC043, LUAD |
| cpg0034-arevalo-su-motive | A graph dataset comprising Cell Painting features for 11,000 genes and 3,600 compounds, along with their relationships extracted from seven publicly available databases | (Arevalo and Su et al., 2024) [Publication](https://proceedings.neurips.cc/paper_files/paper/2024/hash/fdb3fa770c2e0ecbb4b7dc7083ef5be9-Abstract-Datasets_and_Benchmarks_Track.html), [Preprint](https://arxiv.org/abs/2406.08649) | [analysis](https://github.com/carpenter-singh-lab/2024_Arevalo_NeurIPS_MotiVE) | 4.5 GB | 0 GB | 4.5 GB | v3 | |
| cpg0036-EU-OS-bioactives | 2464 compounds from EU-OPENSCREEN Bioactive compound set, four imaging sites, two cell lines (HepG2 & U2OS) | (Wolff et al., 2025) [Publication](https://doi.org/10.1016/j.isci.2025.112445) [Preprint](https://doi.org/10.1101/2024.08.27.609964) | [aggregated profiles](https://doi.org/10.5281/zenodo.13309566), [analysis scripts](https://github.com/schmiedc/EU-OS_bioactives), [compound information](https://www.probes-drugs.org/compounds/standardized#compoundset=353@AND) | 3.5 TB | 3.5 TB | | v1 | Bioactives, EU-OS-Bioactives |
| cpg0038-tegtmeyer-neuropainting | Multiple brain cell types | (Tegtmeyer et al., 2024) [Preprint](https://doi.org/10.1101/2024.11.16.623947), Description of Neuropainting variant | [data](https://github.com/broadinstitute/2019_05_28_Neuronal_Cell_Painting), [analysis](https://github.com/broadinstitute/NeuroPainting) | 2.0 TB | 1.8 TB | 240 GB | neuropainting | |
| cpg0039-garcia-fossa-livecellpainting | Live cell painting of Huh7 cells treated with silver nanoparticles | (Garcia-Fossa et al., 2025) [Publication](https://doi.org/10.1091/mbc.E24-07-0308) | [analysis](https://fefossa.github.io/2023_CourseImageAnalysis_NanoCell/index.html) | 70 GB | 41 GB | 29 GB | live cell painting | |
| cpg0046-microrna | 2,565 human and 1,900 mouse miRNA mimics on 24 million cells across five cell lines | (Wagner et al., 2025) [Preprint](https://doi.org/10.1101/2025.11.14.687149) | [analysis](https://github.com/edbiomedai/microrna-reproducibility) | ~10 TB | ~10 TB | 297 GB | v2 | |
| cpg0049-ipsc-diff-pancreatic-progenitor | iPSC cells differentiated to definitive endoderm and pancreatic progenitors | | | 17.5 TB | 17.5 TB | .6 GB | v2 | |