dataverse 10.18130 V3 B35XWX tab metadata d4d

Datasheet for Dataset - Human Readable Format

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Motivation

Why was the dataset created?

  • Name
    CM4AI Functional Genomics Grand Challenge purpose
    Response
    Provide AI-ready datasets and provenance-rich metadata for mapping human cell architecture and function from disease-relevant cell lines to enable machine learning and AI research.
GrantorGrant NameGrant Number
National Institutes of Health (NIH)Bridge2AI Program-
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Composition

What do the instances represent?

Data TypeNameRepresentation
scRNA-seq-derived perturbation profiles and associated phenotypes.Perturb-seq instancesSingle-cell transcriptional and fitness phenotype profiles from CRISPRi perturbation in undifferenti...
Mass spectrometry chromatographic fractions and protein abundance profiles.SEC-MS instancesProtein complex and interaction measurements from size exclusion chromatography mass spectrometry in...
Multichannel confocal images (DAPI, ER/calreticulin, microtubules/tubulin, protein-of-interest).IF imaging instancesImmunofluorescence confocal microscopy images of MDA-MB-468 cells under paclitaxel and untreated con...
  • Name
    Cell lines and conditions
    Identification
    • Undifferentiated KOLF2.1J iPSCs
    • iPSC-derived NPCs
    • iPSC-derived neurons
    • iPSC-derived cardiomyocytes
    • MDA-MB-468 breast cancer cells
    • Drug Treatments
      vorinostat, paclitaxel; untreated controls
  • Name
    Distribution formats
    Description
    • RO-Crate packaged datasets
    • JSON metadata
    • ZIP archives
    • Public Dataverse repository access
  • Name
    Initial public distribution
    Description
    • 2025-03-03
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Collection Process

How was the data acquired?

doi:10.18130/V3/B35XWX
Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
This dataset is the March 2025 Data Release of Cell Maps for Artificial Intelligence (CM4AI; CM4AI.org), the Functional Genomics Grand Challenge in the NIH Bridge2AI program. This Beta release includes perturb-seq data in undifferentiated KOLF2.1J iPSCs; SEC-MS data in undifferentiated KOLF2.1J iPSCs and iPSC-derived NPCs, neurons, and cardiomyocytes; and IF images in MDA-MB-468 breast cancer cells in the presence and absence of chemotherapy (vorinostat and paclitaxel). CM4AI output data are packaged with provenance graphs and rich metadata as AI-ready datasets in RO-Crate format using the FAIRSCAPE framework. Data presented here will be augmented regularly through the end of the project. CM4AI is a collaboration of UCSD, UCSF, Stanford, UVA, Yale, UA Birmingham, Simon Fraser University, and the Hastings Center. This data is Copyright (c) 2025 The Regents of the University of California except where otherwise noted. Spatial proteomics raw image data is copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University. Dataset licensed for reuse under Creative Commons Attribution-NonCommercial- ShareAlike 4.0 International license (https://creativecommons.org/licenses/by-nc-sa/4.0/). Attribution is required to the copyright holders and the authors. Any publications referencing this data or derived products should cite the Related Publication below, as well as directly citing this data collection (2025-03-04). (2025-03-07)
https://doi.org/10.18130/V3/B35XWX
2025-03-03
  • AI
  • affinity purification
  • AP-MS
  • artificial intelligence
  • breast cancer
  • Bridge2AI
  • cardiomyocyte
  • CM4AI
  • CRISPR/Cas9
  • induced pluripotent stem cell
  • iPSC
  • KOLF2.1J
  • machine learning
  • mass spectroscopy
  • MDA-MB-468
  • neural progenitor cell
  • NPC
  • neuron
  • paclitaxel
  • perturb-seq
  • perturbation sequencing
  • protein-protein interaction
  • protein localization
  • single-cell RNA sequencing
  • scRNAseq
  • SEC-MS
  • size exclusion chromatography
  • subcellular imaging
  • vorinostat
  • Clark T
  • Parker J
  • Al Manir S
  • Axelsson U
  • Ballllosero Navarro F
  • Chinn B
  • Churas CP
  • Dailamy A
  • Doctor Y
  • Fall J
  • Forget A
  • Gao J
  • Hansen JN
  • Hu M
  • Johannesson A
  • Khaliq H
  • Lee YH
  • Lenkiewicz J
  • Levinson MA
  • Marquez C
  • Metallo C
  • Muralidharan M
  • Nourreddine S
  • Niestroy J
  • Obernier K
  • Pan E
  • Polacco B
  • Pratt D
  • Qian G
  • Schaffer L
  • Sigaeva A
  • Thaker S
  • Zhang Y
  • Bélisle-Pipon JC
  • Brandt C
  • Chen JY
  • Ding Y
  • Fodeh S
  • Krogan N
  • Lundberg E
  • Mali P
  • Payne-Foster P
  • Ratcliffe S
  • Ravitsky V
  • Sali A
  • Schulz W
  • Ideker T
https://w3id.org/ro/crate
  • Name
    Gap addressed
    Response
    Deliver standardized, provenance-linked, FAIR AI-ready cellular maps and multimodal assays to address the scarcity of large, interoperable cell atlas datasets for AI development.
RoleNameORCIDAffiliation
ContributorCM4AI Consortium-UCSD
ContributorCM4AI Consortium-UCSF
ContributorCM4AI Consortium-Stanford
ContributorCM4AI Consortium-UVA
ContributorCM4AI Consortium-Yale
ContributorCM4AI Consortium-UA Birmingham
ContributorCM4AI Consortium-Simon Fraser University
ContributorCM4AI Consortium-The Hastings Center
  • Name
    Data collection modalities
    Description
    • CRISPRi perturbation sequencing (perturb-seq)
    • Size exclusion chromatography mass spectrometry (SEC-MS)
    • Immunofluorescence staining and confocal microscopy
  • Name
    March 2025 release
    Description
    • Dataset release labeled "March 2025 Data Release (Beta)"
    • Files published Mar 3, 2025
Name
Copyright statements
Description
  • Copyright (c) 2025 The Regents of the University of California except where otherwise noted.
  • Spatial proteomics raw image data is copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University.
  • Name
    Hosting and access
    Description
    • Hosted and distributed via University of Virginia Dataverse.
CompressionDescriptionFormatIDIssuedMd5Media TypeNamePathTitle
This dataset represents an expressed genome-scale CRISPRi Perturbation Cell Atlas in undifferentiate...JSONdoi:10.18130/V3/B35XWX#ro-crate-crispri-cell-atlas2025-03-03cbdb263b1c099396d75e16f00a79a818application/jsonro-crate-metadata.json (CRISPR Perturbation Cell Atlas)ro-crate-metadata.jsonro-crate-metadata.json
This dataset represents raw sequence data from an expressed genome-scale CRISPRi Perturbation Cell A...JSONdoi:10.18130/V3/B35XWX#ro-crate-crispri-raw2025-03-031cafefa32a897998e3e2ba0a29a3ef5capplication/jsonro-crate-metadata.json (CRISPR Perturbation RNA Sequences - Raw Sequences)ro-crate-metadata.jsonro-crate-metadata.json
ZIPThis data set displays the spatial localization of 563 proteins of interest in cells of the breast c...doi:10.18130/V3/B35XWX#if-images-paclitaxel2025-03-039422486c80bc9e1d35b2fbbc72a5f043application/zipcm4ai-v0.6-beta-if-images-paclitaxel.zipProtein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-paclitaxel.zipcm4ai-v0.6-beta-if-images-paclitaxel.zip
ZIPThis data set displays the spatial localization of 563 proteins of interest in untreated cells of th...doi:10.18130/V3/B35XWX#if-images-untreated2025-03-030b4d129f5fbc3bb7f7ea564cd032cef7application/zipcm4ai-v0.6-beta-if-images-untreated.zipProtein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-untreated.zipcm4ai-v0.6-beta-if-images-untreated.zip
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Uses

What (other) tasks could the dataset be used for?

NameResponse
Task 1Analyze single-cell transcriptional and fitness phenotypes from CRISPRi perturbation (perturb-seq) i...
Task 2Quantify protein complexes and interactions via size exclusion chromatography mass spectrometry (SEC...
Task 3Train and evaluate AI/computer vision methods on immunofluorescence confocal images for protein subc...
  • Name
    Related publication
    Description
    • Clark T, Parker J, Schaffer L, Obernier K, Al Manir S, Churas CP, Dailamy A, Doctor Y, Forget A, Hansen JN, Hu M, Lenkiewicz J, Levinson MA, Marquez C, Nourreddine S, Niestroy J, Pratt D, Qian G, Thaker S, Bélisle-Pipon JC, Brandt C, Chen J, Ding Y, Fodeh S, Krogan N, Lundberg E, Mali P, Payne-Foster P, Ratcliffe S, Ravitsky V, Sali A, Schulz W, Ideker T. Cell Maps for Artificial Intelligence: AI-Ready Maps of Human Cell Architecture from Disease-Relevant Cell Lines. 2024. doi: http://doi.org/10.1101/2024.05.21.589311
  • Name
    License-restricted use
    Description
    • Commercial use is prohibited under CC BY-NC-SA 4.0.
Name
CC BY-NC-SA 4.0
Description
  • Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (https://creativecommons.org/licenses/by-nc-sa/4.0/). Attribution to the copyright holders (The Regents of the University of California; The Board of Trustees of the Leland Stanford Junior University for spatial proteomics raw image data) and the authors is required.
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Distribution

How will the dataset be distributed?

doi:10.18130/V3/B35XWX
https://creativecommons.org/licenses/by-nc-sa/4.0/
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Maintenance

How will the dataset be maintained?

1.4
Name
Update plan
Description
  • Data will be augmented regularly through the end of the project.
  • Collection is under review for potential modification in compliance with Administration directives.
Generated on 2025-11-09 10:17:35 using Bridge2AI Data Sheets Schema