dataverse 10.18130 V3 B35XWX d4d

Datasheet for Dataset - Human Readable Format

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Motivation

Why was the dataset created?

  • Name
    Purpose
    Response
    Provide AI-ready, FAIR, provenance-rich multimodal functional genomics datasets to map human cell architecture and enable machine learning and AI applications.
GrantorGrant NameGrant Number
National Institutes of HealthNIH OT2 award1OT2OD032742-01
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Composition

What do the instances represent?

  • Name
    DistributionFormat
    Description
    • RO-Crate JSON-LD
    • ZIP Archive
  • Name
    DistributionDate
    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
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)
  • CM4AI Consortium
  • Justin Niestroy (Depositor)
2025-02-27
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
en
https://doi.org/10.18130/V3/B35XWX
https://dataverse.lib.virginia.edu
bibo:draft
Cell Maps for Artificial Intelligence (CM4AI) program, NIH Bridge2AI
  • Name
    AddressingGap
    Response
    Bridge the gap between large-scale experimental cell maps and AI by releasing standardized RO-Crate datasets with complete provenance to support reproducibility and downstream AI use.
RoleNameORCIDAffiliation
ContributorClark T-University of Virginia
ContributorParker J-University of California, San Diego
ContributorAl Manir S-University of Virginia
ContributorAxelsson U-KTH Royal Institute of Technology
ContributorBallllosero Navarro F-Stanford University
ContributorChinn B-University of California San Diego
ContributorChuras CP-University of California San Diego
ContributorDailamy A-University of California, San Diego
ContributorDoctor Y-University of California, San Diego
ContributorFall J-KTH - Royal Institute of Technology
ContributorForget A-University of California San Francisco
ContributorGao J-University of California San Diego
ContributorHansen JN-Stanford University
ContributorHu M-University of California San Diego
ContributorJohannesson A-KTH - Royal Institute of Technology
ContributorKhaliq H-University of California San Diego
ContributorLee YH-University of California San Diego
ContributorLenkiewicz J-University of California San Diego
ContributorLevinson MA-University of Virginia
ContributorMarquez C-University of California San Diego
ContributorMetallo C-University of California San Diego
ContributorMuralidharan M-University of California San Francisco
ContributorNourreddine S-University of California San Diego
ContributorNiestroy J-University of Virginia
ContributorObernier K-University of California San Francisco
ContributorPan E-University of California San Diego
ContributorPolacco B-University of California San Francisco
ContributorPratt D-University of California San Diego
ContributorQian G-University of California San Diego
ContributorSchaffer L-University of California San Diego
ContributorSigaeva A-KTH Royal Institute of Technology
ContributorThaker S-University of Alabama at Birmingham
ContributorZhang Y-University of California San Diego
ContributorBĂ©lisle-Pipon JC-Simon Fraser University
ContributorBrandt C-Yale University
ContributorChen JY-The University of Alabama at Birmingham
ContributorDing Y-University of Texas at Austin
ContributorFodeh S-Yale University
ContributorKrogan N-University of California San Francisco
ContributorLundberg E-Stanford University
ContributorMali P-University of California San Diego
ContributorPayne-Foster P-University of Alabama
ContributorRatcliffe S-University of Virginia
ContributorRavitsky V-University of Montreal
ContributorSali A-University of California San Diego
ContributorSchulz W-Yale University
ContributorIdeker T-University of California San Diego
  • Name
    CollectionTimeframe
    Description
    • Data created on 2025-02-27 and first published on 2025-03-03.
  • Name
    CollectionMechanism
    Description
    • CRISPRi perturb-seq in undifferentiated KOLF2.1J hiPSCs.
    • Size exclusion chromatography-mass spectrometry (SEC-MS) in hiPSCs, and iPSC-derived NPCs, neurons, and cardiomyocytes.
    • Immunofluorescence (ICC-IF) confocal microscopy imaging in MDA-MB-468 breast cancer cells, with and without chemotherapy (vorinostat, paclitaxel).
  • Name
    InstanceAcquisition
    Description
    • Directly observed imaging (IF confocal microscopy), mass spectrometry (SEC-MS), and single-cell RNA sequencing (perturb-seq).
    • CRISPRi perturbations to assay transcriptional and fitness phenotypes across 11,739 targeted genes.
  • Name
    DataCollector
    Description
    • Lundberg Lab, Stanford University (IF imaging).
    • Nevan Krogan Laboratory, University of California San Francisco (SEC-MS).
    • University of California San Diego CM4AI team (CRISPRi perturb-seq).
  • Name
    PreprocessingStrategy
    Description
    • RO-Crate packaging with provenance graphs via FAIRSCAPE framework; modality-specific preprocessing is described in individual RO-Crate metadata files.
Name
IPRestrictions
Description
  • Copyright (c) 2025 The Regents of the University of California except where noted. Spatial proteomics raw image data copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University.
Name
ExportControlRegulatoryRestrictions
Description
  • Collection is under review for potential modification in compliance with Administration directives (per repository notice).
DescriptionName
Ideker T (Point of Contact; University of California San Diego) via Dataverse contact.Maintainer
University of Virginia Dataverse SupportMaintainer
Acquisition MethodsCollection MechanismsCompressionData CollectorsDescriptionDistribution DatesExternal ResourcesFormatIDInstancesIssuedMd5Media TypeNamePathTitle
{'name': 'InstanceAcquisition', 'description': ['CRISPRi perturbations with single-cell RNA sequencing readouts in undifferentiated KOLF2.1J hiPSCs.']}{'name': 'CollectionMechanism', 'description': ['Perturb-seq experimental pipeline and RO-Crate packaging.']}{'name': 'DataCollector', 'description': ['University of California San Diego CM4AI team']}This dataset represents an expressed genome-scale CRISPRi Perturbation Cell Atlas in undifferentiate...{'name': 'DistributionDate', 'description': ['2025-03-03']}JSONCRISPR Perturbation Cell Atlas/ro-crate-metadata.json{'name': 'Instance', 'representation': 'CRISPRi perturb-seq profiles and fitness phenotypes in KOLF2.1J hiPSCs', 'data_type': 'Single-cell RNA sequencing-derived gene expression and phenotype summaries', 'counts': 11739}2025-03-03cbdb263b1c099396d75e16f00a79a818application/jsonCRISPR Perturbation Cell Atlas RO-Crate metadataCRISPR Perturbation Cell Atlas/ro-crate-metadata.jsonro-crate-metadata.json (CRISPR Perturbation Cell Atlas)
{'name': 'InstanceAcquisition', 'description': ['Single-cell RNA sequencing following CRISPRi perturbations.']}{'name': 'DataCollector', 'description': ['University of California San Diego CM4AI team']}Raw sequence data from an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J hiPSCs ...{'name': 'DistributionDate', 'description': ['2025-03-03']}JSONCRISPR Perturbation RNA Sequences - Raw Sequences/ro-crate-metadata.json{'name': 'Instance', 'representation': 'Raw RNA sequencing data associated with CRISPRi perturbations in KOLF2.1J hiPSCs', 'data_type': 'Raw sequencing reads metadata (see RO-Crate)', 'counts': 11739}2025-03-031cafefa32a897998e3e2ba0a29a3ef5capplication/jsonCRISPR Perturbation RNA Sequences (Raw) RO-Crate metadataCRISPR Perturbation RNA Sequences - Raw Sequences/ro-crate-metadata.jsonro-crate-metadata.json (CRISPR Perturbation RNA Sequences - Raw Sequences)
{'name': 'CollectionMechanism', 'description': ['ICC-IF staining and confocal microscopy imaging under paclitaxel treatment.']}ZIP{'name': 'DataCollector', 'description': ['Lundberg Lab, Stanford University']}Spatial localization of 563 proteins of interest in MDA-MB-468 cells treated with paclitaxel, imaged...{'name': 'DistributionDate', 'description': ['2025-03-03']}Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-paclitaxel.zip{'name': 'Instance', 'representation': 'Immunofluorescence confocal microscopy images of protein localization in MDA-MB-468 cells (paclitaxel treated)', 'data_type': 'Multichannel TIFF/JPEG images packaged in ZIP (see RO-Crate for specifics)', 'counts': 563}2025-03-039422486c80bc9e1d35b2fbbc72a5f043application/zipProtein Localization Subcellular Images (paclitaxel)Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-paclitaxel.zipcm4ai-v0.6-beta-if-images-paclitaxel.zip
{'name': 'CollectionMechanism', 'description': ['ICC-IF staining and confocal microscopy imaging in untreated condition.']}ZIP{'name': 'DataCollector', 'description': ['Lundberg Lab, Stanford University']}Spatial localization of 563 proteins of interest in untreated MDA-MB-468 cells, imaged by ICC-IF con...{'name': 'DistributionDate', 'description': ['2025-03-03']}Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-untreated.zip{'name': 'Instance', 'representation': 'Immunofluorescence confocal microscopy images of protein localization in MDA-MB-468 cells (untreated controls)', 'data_type': 'Multichannel TIFF/JPEG images packaged in ZIP (see RO-Crate for specifics)', 'counts': 563}2025-03-030b4d129f5fbc3bb7f7ea564cd032cef7application/zipProtein Localization Subcellular Images (untreated)Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-untreated.zipcm4ai-v0.6-beta-if-images-untreated.zip
{'name': 'CollectionMechanism', 'description': ['ICC-IF staining and confocal microscopy imaging under vorinostat treatment.']}ZIP{'name': 'DataCollector', 'description': ['Lundberg Lab, Stanford University']}Spatial localization of 563 proteins of interest in MDA-MB-468 cells treated with vorinostat, imaged...{'name': 'DistributionDate', 'description': ['2025-03-03']}Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-vorinostat.zip{'name': 'Instance', 'representation': 'Immunofluorescence confocal microscopy images of protein localization in MDA-MB-468 cells (vorinostat treated)', 'data_type': 'Multichannel TIFF/JPEG images packaged in ZIP (see RO-Crate for specifics)', 'counts': 563}2025-03-03ac577109a41a9806978461157b777d52application/zipProtein Localization Subcellular Images (vorinostat)Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-vorinostat.zipcm4ai-v0.6-beta-if-images-vorinostat.zip
{'name': 'CollectionMechanism', 'description': ['Size exclusion chromatography followed by mass spectrometry (SEC-MS).']}{'name': 'DataCollector', 'description': ['Nevan Krogan Laboratory, University of California San Francisco']}Size exclusion chromatography–mass spectrometry (SEC-MS) dataset in undifferentiated KOLF2.1J hiPSCs...{'name': 'DistributionDate', 'description': ['2025-03-03']}{'name': 'ExternalResource', 'external_resources': ['PRIDE repository (planned archival)'], 'future_guarantees': ['Repository submission planned when available.'], 'archival': ['Hosted on UVA Dataverse; PRIDE archival forthcoming.'], 'restrictions': ['CC BY-NC-SA 4.0 license applies.']}JSONProtein-protein Interaction SEC-MS/ro-crate-metadata.json{'name': 'Instance', 'representation': 'SEC-MS protein complex profiles in KOLF2.1J hiPSCs and iPSC-derived lineages', 'data_type': 'Mass spectrometry fractionation profiles (see RO-Crate)'}2025-03-03cb67e7749b15ce87b9042a9feba9d032application/jsonProtein–protein Interaction SEC-MS RO-Crate metadataProtein-protein Interaction SEC-MS/ro-crate-metadata.jsonro-crate-metadata.json (Protein–protein Interaction SEC-MS)
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Uses

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

  • Name
    Task
    Response
    Train and benchmark AI/ML models for cellular phenotype prediction, protein localization, and protein interaction inference using perturb-seq, SEC-MS, and IF imaging.
  • Name
    ExistingUse
    Description
    • Related Publications
      2024 preprints cited in the dataset record (bioRxiv doi:10.1101/2024.05.21.589311; doi:10.1101/2024.11.03.621734).
  • Name
    OtherTask
    Description
    • Multimodal integration, network inference, phenotype prediction, and benchmarking AI readiness of cell maps.
  • Name
    FutureUseImpact
    Description
    • Dataset will be augmented regularly; users should monitor versions and provenance to ensure comparability across releases.
Name
LicenseAndUseTerms
Description
  • Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Attribution required to the copyright holders and authors. https://creativecommons.org/licenses/by-nc-sa/4.0/
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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/
Name
VersionAccess
Description
  • Hosted on Dataverse with versioned releases; older versions remain accessible per repository policies.
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Maintenance

How will the dataset be maintained?

1.4
Name
UpdatePlan
Description
  • Data will be augmented regularly through the end of the project; users should check the Dataverse record for updated versions.
Generated on 2025-11-09 10:17:34 using Bridge2AI Data Sheets Schema