# dataverse 10.18130 V3 B35XWX tab metadata d4d

Datasheet for Dataset - Human Readable Format

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## Motivation

Why was the dataset created?

Purposes

- 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.

Funders

Grantor | Grant Name | Grant Number
--- | --- | ---
National Institutes of Health | Bridge2AI Functional Genomics Grand Challenge | 1OT2OD032742-01

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## Composition

What do the instances represent?

Instances

Data Type | Name | Representation
--- | --- | ---
Raw and processed single-cell RNA counts/metadata with associated perturbation identifiers and fitne... | Perturb-seq scRNA-seq profiles | Single-cell transcriptomic profiles from CRISPRi perturbations in KOLF2.1J hiPSCs
Sequencing reads and associated RO-Crate metadata | Raw RNA sequencing reads | Raw RNA sequence data from CRISPRi perturbation experiments
MS feature intensities/fractionation profiles and associated metadata | SEC-MS protein interaction measurements | Protein complex profiles across size exclusion chromatography fractions measured by mass spectrometr...
Image files (ZIP archives) and associated RO-Crate metadata | Immunofluorescence microscopy images | Multichannel confocal images of subcellular protein localization in MDA-MB-468 cells under drug pert...

Instance Acquisition Methods

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

Distribution Formats

- 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

Distribution Dates

- Description
    2025-03-03

🔍

## Collection Process

How was the data acquired?

ID *
doi:10.18130/V3/B35XWX
Name
Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
Title
Cell Maps for Artificial Intelligence - March 2025 Data Release (Beta)
Description
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.
Page
https://doi.org/10.18130/V3/B35XWX
Issued
2025-03-03
Created On
2025-02-27
Publisher
https://dataverse.lib.virginia.edu
Language
en
Conforms To
https://w3id.org/ro/crate
Keywords

- 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

Resources

Compression | Description | Distribution Dates | Format | ID | Is Tabular | License | Md5 | Media Type | Name | Title
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
| RO-Crate metadata for an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J hiPSCs m... | {'description': '2025-03-03'} | JSON | doi:10.18130/V3/B35XWX#crisper-perturbation-cell-atlas-ro-crate-metadata |  | CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/) | cbdb263b1c099396d75e16f00a79a818 | application/json | ro-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'} | JSON | doi:10.18130/V3/B35XWX#crisper-perturbation-rna-raw-ro-crate-metadata |  | CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/) | 1cafefa32a897998e3e2ba0a29a3ef5c | application/json | ro-crate-metadata.json (CRISPR Perturbation RNA Sequences - Raw Sequences) | CRISPR Perturbation RNA Sequences - Raw Sequences RO-Crate metadata
ZIP | Immunofluorescence confocal images showing spatial localization of 563 proteins in MDA-MB-468 cells ... | {'description': '2025-03-03'} |  | doi:10.18130/V3/B35XWX#if-images-paclitaxel | no | CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/) | 9422486c80bc9e1d35b2fbbc72a5f043 | application/zip | cm4ai-v0.6-beta-if-images-paclitaxel.zip | Protein Localization Subcellular Images — paclitaxel-treated MDA-MB-468
ZIP | Immunofluorescence confocal images showing spatial localization of 563 proteins in untreated MDA-MB-... | {'description': '2025-03-03'} |  | doi:10.18130/V3/B35XWX#if-images-untreated | no | CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/) | 0b4d129f5fbc3bb7f7ea564cd032cef7 | application/zip | cm4ai-v0.6-beta-if-images-untreated.zip | Protein Localization Subcellular Images — untreated MDA-MB-468
ZIP | Immunofluorescence confocal images showing spatial localization of 563 proteins in MDA-MB-468 cells ... | {'description': '2025-03-03'} |  | doi:10.18130/V3/B35XWX#if-images-vorinostat | no | CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/) | ac577109a41a9806978461157b777d52 | application/zip | cm4ai-v0.6-beta-if-images-vorinostat.zip | Protein 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'} | JSON | doi:10.18130/V3/B35XWX#sec-ms-ro-crate-metadata |  | CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/) | cb67e7749b15ce87b9042a9feba9d032 | application/json | ro-crate-metadata.json (Protein-protein Interaction SEC-MS) | Protein-protein Interaction SEC-MS RO-Crate metadata

Addressing Gaps

- Response
    Provide standardized, provenance-rich, multimodal functional genomics datasets to enable AI methods for mapping human cell architecture.

Creators

Role | Name | ORCID | Affiliation
--- | --- | --- | ---
Contributor | Clark T | - | University of Virginia
Contributor | Parker J | - | University of California San Diego
Contributor | Al Manir S | - | University of Virginia
Contributor | Axelsson U | - | KTH Royal Institute of Technology
Contributor | Ballllosero Navarro F | - | Stanford University
Contributor | Chinn B | - | University of California San Diego
Contributor | Churas CP | - | University of California San Diego
Contributor | Dailamy A | - | University of California, San Diego
Contributor | Doctor Y | - | University of California, San Diego
Contributor | Fall J | - | KTH Royal Institute of Technology
Contributor | Forget A | - | University of California San Francisco
Contributor | Gao J | - | University of California San Diego
Contributor | Hansen JN | - | Stanford University
Contributor | Hu M | - | University of California San Diego
Contributor | Johannesson A | - | KTH - Royal Institute of Technology
Contributor | Khaliq H | - | University of California San Diego
Contributor | Lee YH | - | University of California San Diego
Contributor | Lenkiewicz J | - | University of California San Diego
Contributor | Levinson MA | - | University of Virginia
Contributor | Marquez C | - | University of California San Diego
Contributor | Metallo C | - | University of California San Diego
Contributor | Muralidharan M | - | University of California San Francisco
Contributor | Nourreddine S | - | University of California San Diego
Contributor | Niestroy J | - | University of Virginia
Contributor | Obernier K | - | University of California San Francisco
Contributor | Pan E | - | University of California San Diego
Contributor | Polacco B | - | University of California San Francisco
Contributor | Pratt D | - | University of California San Diego
Contributor | Qian G | - | University of California San Diego
Contributor | Schaffer L | - | University of California San Diego
Contributor | Sigaeva A | - | KTH Royal Institute of Technology
Contributor | Thaker S | - | University of Alabama at Birmingham
Contributor | Zhang Y | - | University of California San Diego
Contributor | Bélisle-Pipon JC | - | Simon Fraser University
Contributor | Brandt C | - | Yale University
Contributor | Chen JY | - | The University of Alabama at Birmingham
Contributor | Ding Y | - | University of Texas at Austin
Contributor | Fodeh S | - | Yale University
Contributor | Krogan N | - | University of California San Francisco
Contributor | Lundberg E | - | Stanford University
Contributor | Mali P | - | University of California San Diego
Contributor | Payne-Foster P | - | University of Alabama
Contributor | Ratcliffe S | - | University of Virginia
Contributor | Ravitsky V | - | University of Montreal
Contributor | Sali A | - | University of California San Diego
Contributor | Schulz W | - | Yale University
Contributor | Ideker T | - | University of California San Diego

Collection Mechanisms

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

Collection Timeframes

- Description
    - Data created 2025-02-27; published 2025-03-03; dataset notes updated 2025-03-07

Ethical Reviews
Data Protection Impacts

- Description
    - Dataset comprises measurements from established human cell lines and iPSCs; no direct personal identifiers are included.

Is Deidentified

Name
  Deidentification assessment
Description
  - No personally identifying information; data are derived from cell lines and do not contain direct identifiers.

Ip Restrictions

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.

Regulatory Restrictions
Maintainers

- 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?

Tasks

Name | Response
--- | ---
Perturb-seq analysis | Genome-scale CRISPRi perturbation and single-cell transcriptomic profiling in KOLF2.1J hiPSCs.
Protein-protein interaction mapping | Size exclusion chromatography–mass spectrometry (SEC-MS) to profile protein complexes across fractio...
Subcellular protein localization imaging | Immunofluorescence confocal microscopy of MDA-MB-468 cells under drug perturbations (vorinostat, pac...
AI/ML benchmarking | Use of AI-ready data packages with provenance for machine learning tasks (representation learning, p...

License And Use Terms

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.

Existing Uses

- Description
    - Related publications include the CM4AI preprints describing AI-ready maps and the perturbation cell atlas (bioRxiv DOIs provided in dataset metadata).

Use Repository

- 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
doi:10.18130/V3/B35XWX
License
CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/)
Version Access

Name
  Dataverse versioning
Description
  - Dataset managed in Dataverse with version history; current release labeled Version 1.4.

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## Maintenance

How will the dataset be maintained?

Last Updated On
2025-03-07
Version
1.4
Updates

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