# dataverse 10.18130 V3 F3TD5R d4d

Datasheet for Dataset - Human Readable Format

🎯

## Motivation

Why was the dataset created?

Purposes

- Name
    Intended Purpose
  Response
    AI-ready datasets to support research in functional genomics

Funders

Grantor | Grant Name | Grant Number
--- | --- | ---
National Institutes of Health | 1OT2OD032742-01 | 1OT2OD032742-01

📊

## Composition

What do the instances represent?

Instances

1. Name
     Data Modalities and Instances
   Representation
     Multimodal cellular measurements from human cell lines (iPSCs and disease-relevant lines)
   Instance Type
     Perturb-seq (scRNA-seq), SEC-MS protein-protein interaction profiling, immunofluorescence (IF) images
   Data Type
     Mixture of raw data (images, sequencing reads hosted externally) and processed data/metadata packaged via RO-Crate and Dataverse artifacts
   Sampling Strategies
     1. Name
          Sampling and Representativeness
        Is Sample
          - True
        Is Random
          - False
        Source Data
          - Commercially available de-identified human cell lines (e.g., KOLF2.1J iPSCs; MDA-MB-468)
        Is Representative
          - False
        Why Not Representative
          - Does not represent all biological variants seen in the wider population
        Strategies
          - Targeted selection of proteins and perturbations across specified cell types and treatments
   Missing Information
     - Name
         Known Omissions
       Missing
         - Computed cell maps not included in this release
       Why Missing
         - To be added in future releases

Subpopulations

- Name
    Cell Types and Conditions
  Identification
    - Undifferentiated KOLF2.1J iPSCs
    - iPSC-derived NPCs
    - iPSC-derived neurons
    - iPSC-derived cardiomyocytes
    - MDA-MB-468 breast cancer cells (treated and untreated)
  Distribution
    - Overlapping but non-identical protein sets across SEC-MS, IF, and perturb-seq modalities

Distribution Formats

- Name
    Distribution Channels and Formats
  Description
    - Dataverse package with RO-Crate metadata, HTML datasheet, provenance graphs, and ZIP archives of images
    - External repositories for raw modality data (SRA, MassIVE)

Distribution Dates

Description | Name
--- | ---
2025-07-01 | Initial Release
2025-10-22 | Additional Image Archives

Distribution

- Description
    The dataset is hosted publicly on Dataverse; some subsets may be under temporary embargo.

🔍

## Collection Process

How was the data acquired?

ID *
doi:10.18130/V3/F3TD5R
Name
Cell Maps for Artificial Intelligence - June 2025 Data Release (Beta)
Title
Cell Maps for Artificial Intelligence - June 2025 Data Release (Beta)
Description
This dataset is the June 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, iPSC-derived NPCs, neurons, cardiomyocytes, and treated and untreated MDA-MB-468 breast cancer cells; and IF images in MDA-MB-468 breast cancer cells in the presence and absence of chemotherapy (vorinostat and paclitaxel).
Page
https://doi.org/10.18130/V3/F3TD5R
Issued
2025-07-01
Created On
2025-02-27
Keywords

- AI
- artificial intelligence
- machine learning
- Bridge2AI
- CM4AI
- induced pluripotent stem cell
- iPSC
- KOLF2.1J
- neural progenitor cell
- NPC
- neuron
- cardiomyocyte
- breast cancer
- MDA-MB-468
- paclitaxel
- vorinostat
- perturb-seq
- perturbation sequencing
- single-cell RNA sequencing
- scRNAseq
- SEC-MS
- size exclusion chromatography
- protein-protein interaction
- affinity purification
- AP-MS
- mass spectroscopy
- protein localization
- subcellular imaging

Created By

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

Addressing Gaps

- Name
    Gap Addressed
  Response
    Provide interoperable, AI-ready multimodal cellular data across perturb-seq, SEC-MS, and IF imaging modalities

External Resources

1. Name
     External Data Links
   External Resources
     - Sequence Read Archive (sra) Data
         NCBI BioProject
     - Mass Spectrometry Data (human Ipscs)
         MassIVE Repository
     - Mass Spectrometry Data (human Cancer Cells)
         MassIVE Repository
   Archival
     - Long-term preservation at University of Virginia Dataverse; external repositories host raw modality data
   Restrictions
     - Some datasets under temporary pre-publication embargo

Is Deidentified

Name
  De-identification
Description
  - Human Subjects
      False
  - De Identified Samples
      True
  - Fda Regulated
      False

Confidential Elements

- Name
    Confidentiality
  Description
    - No PII; de-identified human cell line data

Sensitive Elements

- Name
    Sensitivity
  Description
    - Biomedical laboratory data; not suitable for clinical decision-making without appropriate oversight

Acquisition Methods

1. Name
     Data Acquisition
   Description
     - High-throughput laboratory measurements including single-cell RNA sequencing (perturb-seq), size exclusion chromatography mass spectrometry (SEC-MS), and immunofluorescence imaging
   Was Directly Observed
     True
   Was Reported By Subjects
     False
   Was Inferred Derived
     Some processed outputs; primary raw measurements acquired directly
   Was Validated Verified
     Not specified in this record

Collection Mechanisms

- Name
    Collection Mechanisms
  Description
    - Laboratory apparatuses and protocols (sequencing instruments for perturb-seq, mass spectrometers for SEC-MS, confocal microscopy for IF); provenance graphs included for some subsets

Data Collectors

- Name
    Contributing Institutions
  Description
    - University of California San Diego; University of California San Francisco; Stanford University; University of Virginia; KTH Royal Institute of Technology; University of Alabama at Birmingham; Yale University; Simon Fraser University; University of Montreal; University of Texas at Austin

Collection Timeframes

- Name
    Timeframe
  Description
    - Data Creation Date
        2025-02-27; Release publication date: 2025-07-01; Content current as of 2025-06-30; additional image archives published 2025-10-22

Ethical Reviews

- Name
    Ethical Review and Governance
  Description
    - Data Governance Committee
        Jillian Parker (jillianparker@health.ucsd.edu)
    - Ethical Review
        Vardit Ravitsky (ravitskyv@thehastingscenter.org) and Jean-Christophe Belisle-Pipon (jean-christophe_belisle-pipon@sfu.ca)

Preprocessing Strategies

- Name
    Packaging/Metadata
  Description
    - Release provided with RO-Crate metadata and provenance graphs to support reproducibility and reuse

Raw Sources

- Name
    Raw Data Availability
  Description
    - Raw Or Primary Modality Data Accessible Via External Repositories
        SRA BioProject (sequencing) and MassIVE (mass spectrometry)

Maintainers

Description | Name
--- | ---
Long term preservation in the University of Virginia Dataverse, supported by committed institutional funds | University of Virginia Dataverse
Use Dataverse contact; Project Lead listed as Trey Ideker (UC San Diego) | Point of Contact

Subsets

Compression | Description | Format | ID | Issued | Md5 | Media Type | Name | Path
--- | --- | --- | --- | --- | --- | --- | --- | ---
| HTML datasheet summarizing key release information. |  | release-ro-crate-datasheet.html | 2025-07-01 | 599c9ece9b88b3ce797b82463b4a1eb4 | text/html | release-ro-crate-datasheet.html | release-ro-crate-datasheet.html
| Release RO-Crate with pointers to sub ro-crates. | JSON | release-ro-crate-metadata.json | 2025-07-01 | 99f9e00053bff3020fd9832a3a518bbb | application/json | release-ro-crate-metadata.json | release-ro-crate-metadata.json
ZIP | This dataset displays the spatial localization of 464 proteins of interest in MDA-MB-468 cells treat... |  | cm4ai-ifimages-mda-mb-468-paclitaxel.zip | 2025-10-22 | 0d972b80744344ddeede516a0cf6e3d7 | application/zip | cm4ai-ifimages-mda-mb-468-paclitaxel.zip | Images/cm4ai-ifimages-mda-mb-468-paclitaxel.zip
ZIP | Spatial localization of 464 proteins in untreated MDA-MB-468 cells, imaged by ICC-IF and confocal mi... |  | cm4ai-ifimages-mda-mb-468-untreated.zip | 2025-10-22 | a98affcc05429650c6bb3906cd836d55 | application/zip | cm4ai-ifimages-mda-mb-468-untreated.zip | Images/cm4ai-ifimages-mda-mb-468-untreated.zip
ZIP | Spatial localization of 464 proteins in MDA-MB-468 cells treated with vorinostat, imaged by ICC-IF a... |  | cm4ai-ifimages-mda-mb-468-vorinostat.zip | 2025-10-22 | ad4e68ccc14b0f3349dad3321e7b81b2 | application/zip | cm4ai-ifimages-mda-mb-468-vorinostat.zip | Images/cm4ai-ifimages-mda-mb-468-vorinostat.zip
| Provenance graph for paclitaxel-treated image subset (download to view). |  | Images-paclitaxel-provenance-graph.html | 2025-07-01 | e38e63e4c8dfc5808a5ffa2d7829fc38 | text/html | Images-paclitaxel-provenance-graph.html | Images/paclitaxel/Images-paclitaxel-provenance-graph.html
| Provenance graph for untreated image subset (download to view). |  | Images-untreated-provenance-graph.html | 2025-07-01 | 1a3b510f74d3f8647e07c6559ce64ee8 | text/html | Images-untreated-provenance-graph.html | Images/untreated/Images-untreated-provenance-graph.html
| Provenance graph for vorinostat-treated image subset (download to view). |  | Images-vorinostat-provenance-graph.html | 2025-07-01 | 58935fe4e254b31d33fed019f24c7668 | text/html | Images-vorinostat-provenance-graph.html | Images/vorinostat/Images-vorinostat-provenance-graph.html
| Provenance graph for mass spectrometry data (cancer cells) (download to view). |  | mass-spec-cancer-cells-provenance-graph.html | 2025-07-01 | 931ad9b552562024cb84ebe62d1f1838 | text/html | mass-spec-cancer-cells-provenance-graph.html | mass-spec/cancer-cells/mass-spec-cancer-cells-provenance-graph.html
| RO-Crate metadata for mass spectrometry (cancer cells). | JSON | mass-spec-cancer-cells-ro-crate-metadata.json |  | 3a7063bb391ea5e05a32ba5da5f4b2f8 | application/json | mass-spec-cancer-cells-ro-crate-metadata.json | mass-spec/cancer-cells/mass-spec-cancer-cells-ro-crate-metadata.json

Content Warnings

- Name
    Usage Warning
  Warnings
    - Large files; Dataverse may require selective downloads or Data Access API for programmatic access

Regulatory Restrictions

Name
  Regulatory Restrictions
Description
  - None specified in this record

Is Tabular
no
🚀

## Uses

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

Tasks

Name | Response
--- | ---
Primary Task | AI model training on functional genomics data
Secondary Task | Cellular process analysis and mapping of cell architecture under disease, treatment, or genetic pert...

Existing Uses

- Name
    Related Publications
  Description
    - Clark T Et Al. 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
    - Nourreddine S Et Al. A Perturbation Cell Atlas Of Human Induced Pluripotent Stem Cells. Biorxiv. 2024. DOI
        https://doi.org/10.1101/2024.11.03.621734

Other Tasks

- Name
    Additional Potential Tasks
  Description
    - Cellular process analysis
    - Analysis of cell architectural changes and interactions under disease processes, treatment conditions, or genetic perturbations

Future Use Impacts

- Name
    Limitations and Biases
  Description
    - Interim release; computed cell maps not yet included
    - Protein sets interrogated by different modalities incompletely overlap
    - Data derived from commercially available de-identified human cell lines; does not represent all biological variants

Discouraged Uses

- Name
    Prohibited Uses
  Description
    - Not to be used in clinical decision-making or any context involving patient care without appropriate regulatory oversight and approval

License And Use Terms

Name
  License
Description
  - CC BY-NC-SA 4.0
  - Community norms expect proper citation of the dataset

Use Repository

- Name
    Dataset Landing Page
  Description
    - University of Virginia Dataverse (see DOI landing page for access and file selection)

📤

## Distribution

How will the dataset be distributed?

DOI
doi:10.18130/V3/F3TD5R
License
CC BY-NC-SA 4.0
🔄

## Maintenance

How will the dataset be maintained?

Last Updated On
2025-10-22
Version
2.0
Updates

Name
  Maintenance Plan
Description
  - Dataset will be regularly updated and augmented through the end of the project in November 2026
  - Updates on a quarterly basis

Generated on 2025-11-09 10:17:34 using Bridge2AI Data Sheets Schema