dataverse 10.18130 V3 B35XWX tab metadata d4d

Datasheet for Dataset - Human Readable Format

🎯

Motivation

Why was the dataset created?

  • Name
    CM4AI Functional Genomics Grand Challenge
    Response
    Create AI-ready, FAIR RO-Crate datasets of multimodal cell maps from disease-relevant human cell lines for AI/ML research and benchmarking.
GrantorGrant NameGrant Number
National Institutes of HealthBridge2AI Functional Genomics Grand Challenge1OT2OD032742-01
📊

Composition

What do the instances represent?

Data TypeNameRepresentation
Raw and processed single-cell RNA counts/metadata with associated perturbation identifiers and fitne...Perturb-seq scRNA-seq profilesSingle-cell transcriptomic profiles from CRISPRi perturbations in KOLF2.1J hiPSCs
Sequencing reads and associated RO-Crate metadataRaw RNA sequencing readsRaw RNA sequence data from CRISPRi perturbation experiments
MS feature intensities/fractionation profiles and associated metadataSEC-MS protein interaction measurementsProtein complex profiles across size exclusion chromatography fractions measured by mass spectrometr...
Image files (ZIP archives) and associated RO-Crate metadataImmunofluorescence microscopy imagesMultichannel confocal images of subcellular protein localization in MDA-MB-468 cells under drug pert...
  1. Description
    • Directly observed molecular and imaging measurements; perturbation identities controlled experimentally; validation via phenotypic, protein-interaction, and metabolic tracing assays
    Was Directly Observed
    True
    Was Reported By Subjects
    False
    Was Inferred Derived
    True
    Was Validated Verified
    True
  • Description
    • Public files available via University of Virginia Dataverse (web UI and Data Access API)
    • RO-Crate JSON metadata
    • ZIP archives for large imaging datasets
  • Description
    2025-03-03
🔍

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. Attribution is required to the copyright holders and the authors. Any publications referencing this data or derived products should cite the related publications and directly cite this data collection.
https://doi.org/10.18130/V3/B35XWX
2025-03-03
2025-02-27
https://dataverse.lib.virginia.edu
en
https://w3id.org/ro/crate
  • AI
  • artificial intelligence
  • machine learning
  • Bridge2AI
  • CM4AI
  • perturb-seq
  • perturbation sequencing
  • single-cell RNA sequencing
  • scRNAseq
  • CRISPR/Cas9
  • induced pluripotent stem cell
  • iPSC
  • KOLF2.1J
  • protein-protein interaction
  • SEC-MS
  • size exclusion chromatography
  • affinity purification
  • AP-MS
  • mass spectroscopy
  • protein localization
  • subcellular imaging
  • immunofluorescence
  • confocal microscopy
  • breast cancer
  • MDA-MB-468
  • cardiomyocyte
  • neural progenitor cell
  • NPC
  • neuron
  • paclitaxel
  • vorinostat
CompressionDescriptionDistribution DatesFormatIDIs TabularLicenseMd5Media TypeNameTitle
RO-Crate metadata for an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J hiPSCs m...{'description': '2025-03-03'}JSONdoi:10.18130/V3/B35XWX#crisper-perturbation-cell-atlas-ro-crate-metadataCC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)cbdb263b1c099396d75e16f00a79a818application/jsonro-crate-metadata.json (CRISPR Perturbation Cell Atlas)CRISPR Perturbation Cell Atlas RO-Crate metadata
RO-Crate metadata for raw sequence data from the CRISPRi Perturbation Cell Atlas in KOLF2.1J hiPSCs.{'description': '2025-03-03'}JSONdoi:10.18130/V3/B35XWX#crisper-perturbation-rna-raw-ro-crate-metadataCC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)1cafefa32a897998e3e2ba0a29a3ef5capplication/jsonro-crate-metadata.json (CRISPR Perturbation RNA Sequences - Raw Sequences)CRISPR Perturbation RNA Sequences - Raw Sequences RO-Crate metadata
ZIPImmunofluorescence confocal images showing spatial localization of 563 proteins in MDA-MB-468 cells ...{'description': '2025-03-03'}doi:10.18130/V3/B35XWX#if-images-paclitaxelnoCC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)9422486c80bc9e1d35b2fbbc72a5f043application/zipcm4ai-v0.6-beta-if-images-paclitaxel.zipProtein Localization Subcellular Images — paclitaxel-treated MDA-MB-468
ZIPImmunofluorescence confocal images showing spatial localization of 563 proteins in untreated MDA-MB-...{'description': '2025-03-03'}doi:10.18130/V3/B35XWX#if-images-untreatednoCC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)0b4d129f5fbc3bb7f7ea564cd032cef7application/zipcm4ai-v0.6-beta-if-images-untreated.zipProtein Localization Subcellular Images — untreated MDA-MB-468
ZIPImmunofluorescence confocal images showing spatial localization of 563 proteins in MDA-MB-468 cells ...{'description': '2025-03-03'}doi:10.18130/V3/B35XWX#if-images-vorinostatnoCC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)ac577109a41a9806978461157b777d52application/zipcm4ai-v0.6-beta-if-images-vorinostat.zipProtein Localization Subcellular Images — vorinostat-treated MDA-MB-468
RO-Crate metadata for size exclusion chromatography–mass spectroscopy (SEC-MS) in KOLF2.1J hiPSCs (w...{'description': '2025-03-03'}JSONdoi:10.18130/V3/B35XWX#sec-ms-ro-crate-metadataCC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)cb67e7749b15ce87b9042a9feba9d032application/jsonro-crate-metadata.json (Protein-protein Interaction SEC-MS)Protein-protein Interaction SEC-MS RO-Crate metadata
  • Response
    Provide standardized, provenance-rich, multimodal functional genomics datasets to enable AI methods for mapping human cell architecture.
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
ContributorBélisle-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
Description
CRISPRi screening with single-cell RNA-seq (perturb-seq)
Size exclusion chromatography coupled to mass spectrometry (SEC-MS)
Immunofluorescence-based staining (ICC-IF) and confocal microscopy
  • Description
    • Data created 2025-02-27; published 2025-03-03; dataset notes updated 2025-03-07
  • Description
    • Dataset comprises measurements from established human cell lines and iPSCs; no direct personal identifiers are included.
Name
Deidentification assessment
Description
  • No personally identifying information; data are derived from cell lines and do not contain direct identifiers.
Name
Copyright notices
Description
  • Copyright (c) 2025 The Regents of the University of California except where otherwise noted.
  • Spatial proteomics raw image data copyright (c) 2025 The Board of Trustees of the Leland Stanford Junior University.
  • Description
    • University of Virginia Dataverse (repository); point of contact via Dataverse messaging
    • Point Of Contact Listed
      Trey Ideker (University of California San Diego)
🚀

Uses

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

NameResponse
Perturb-seq analysisGenome-scale CRISPRi perturbation and single-cell transcriptomic profiling in KOLF2.1J hiPSCs.
Protein-protein interaction mappingSize exclusion chromatography–mass spectrometry (SEC-MS) to profile protein complexes across fractio...
Subcellular protein localization imagingImmunofluorescence confocal microscopy of MDA-MB-468 cells under drug perturbations (vorinostat, pac...
AI/ML benchmarkingUse of AI-ready data packages with provenance for machine learning tasks (representation learning, p...
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 required to copyright holders and authors; cite related publications and this dataset collection.
  • Description
    • Related publications include the CM4AI preprints describing AI-ready maps and the perturbation cell atlas (bioRxiv DOIs provided in dataset metadata).
  • Description
    • Dataset landing page and metadata available at https://doi.org/10.18130/V3/B35XWX; files accessible via Dataverse UI and Data Access API (https://dataverse.lib.virginia.edu/api/access/datafile/)
📤

Distribution

How will the dataset be distributed?

doi:10.18130/V3/B35XWX
CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)
Name
Dataverse versioning
Description
  • Dataset managed in Dataverse with version history; current release labeled Version 1.4.
🔄

Maintenance

How will the dataset be maintained?

2025-03-07
1.4
Name
Update plan
Description
  • Data will be augmented regularly through the end of the project; additional SEC-MS data to be uploaded to PRIDE when available.
Generated on 2025-11-09 10:17:35 using Bridge2AI Data Sheets Schema