# dataverse 10.18130 V3 B35XWX tab metadata d4d

Datasheet for Dataset - Human Readable Format

🎯

## Motivation

Why was the dataset created?

Purposes

- 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.

Funders

Grantor | Grant Name | Grant Number
--- | --- | ---
National Institutes of Health (NIH) | Bridge2AI Program | -

📊

## Composition

What do the instances represent?

Instances

Data Type | Name | Representation
--- | --- | ---
scRNA-seq-derived perturbation profiles and associated phenotypes. | Perturb-seq instances | Single-cell transcriptional and fitness phenotype profiles from CRISPRi perturbation in undifferenti...
Mass spectrometry chromatographic fractions and protein abundance profiles. | SEC-MS instances | Protein complex and interaction measurements from size exclusion chromatography mass spectrometry in...
Multichannel confocal images (DAPI, ER/calreticulin, microtubules/tubulin, protein-of-interest). | IF imaging instances | Immunofluorescence confocal microscopy images of MDA-MB-468 cells under paclitaxel and untreated con...

Subpopulations

- 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

Distribution Formats

- Name
    Distribution formats
  Description
    - RO-Crate packaged datasets
    - JSON metadata
    - ZIP archives
    - Public Dataverse repository access

Distribution Dates

- Name
    Initial public distribution
  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 (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)
Page
https://doi.org/10.18130/V3/B35XWX
Issued
2025-03-03
Keywords

- 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

Created By

- 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

Conforms To
https://w3id.org/ro/crate
Addressing Gaps

- 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.

Creators

Role | Name | ORCID | Affiliation
--- | --- | --- | ---
Contributor | CM4AI Consortium | - | UCSD
Contributor | CM4AI Consortium | - | UCSF
Contributor | CM4AI Consortium | - | Stanford
Contributor | CM4AI Consortium | - | UVA
Contributor | CM4AI Consortium | - | Yale
Contributor | CM4AI Consortium | - | UA Birmingham
Contributor | CM4AI Consortium | - | Simon Fraser University
Contributor | CM4AI Consortium | - | The Hastings Center

Collection Mechanisms

- Name
    Data collection modalities
  Description
    - CRISPRi perturbation sequencing (perturb-seq)
    - Size exclusion chromatography mass spectrometry (SEC-MS)
    - Immunofluorescence staining and confocal microscopy

Collection Timeframes

- Name
    March 2025 release
  Description
    - Dataset release labeled "March 2025 Data Release (Beta)"
    - Files published Mar 3, 2025

Ip Restrictions

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.

Maintainers

- Name
    Hosting and access
  Description
    - Hosted and distributed via University of Virginia Dataverse.

Resources

Compression | Description | Format | ID | Issued | Md5 | Media Type | Name | Path | Title
--- | --- | --- | --- | --- | --- | --- | --- | --- | ---
| This dataset represents an expressed genome-scale CRISPRi Perturbation Cell Atlas in undifferentiate... | JSON | doi:10.18130/V3/B35XWX#ro-crate-crispri-cell-atlas | 2025-03-03 | cbdb263b1c099396d75e16f00a79a818 | application/json | ro-crate-metadata.json (CRISPR Perturbation Cell Atlas) | ro-crate-metadata.json | ro-crate-metadata.json
| This dataset represents raw sequence data from an expressed genome-scale CRISPRi Perturbation Cell A... | JSON | doi:10.18130/V3/B35XWX#ro-crate-crispri-raw | 2025-03-03 | 1cafefa32a897998e3e2ba0a29a3ef5c | application/json | ro-crate-metadata.json (CRISPR Perturbation RNA Sequences - Raw Sequences) | ro-crate-metadata.json | ro-crate-metadata.json
ZIP | This data set displays the spatial localization of 563 proteins of interest in cells of the breast c... |  | doi:10.18130/V3/B35XWX#if-images-paclitaxel | 2025-03-03 | 9422486c80bc9e1d35b2fbbc72a5f043 | application/zip | cm4ai-v0.6-beta-if-images-paclitaxel.zip | Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-paclitaxel.zip | cm4ai-v0.6-beta-if-images-paclitaxel.zip
ZIP | This data set displays the spatial localization of 563 proteins of interest in untreated cells of th... |  | doi:10.18130/V3/B35XWX#if-images-untreated | 2025-03-03 | 0b4d129f5fbc3bb7f7ea564cd032cef7 | application/zip | cm4ai-v0.6-beta-if-images-untreated.zip | Protein Localization Subcellular Images/cm4ai-v0.6-beta-if-images-untreated.zip | cm4ai-v0.6-beta-if-images-untreated.zip

🚀

## Uses

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

Tasks

Name | Response
--- | ---
Task 1 | Analyze single-cell transcriptional and fitness phenotypes from CRISPRi perturbation (perturb-seq) i...
Task 2 | Quantify protein complexes and interactions via size exclusion chromatography mass spectrometry (SEC...
Task 3 | Train and evaluate AI/computer vision methods on immunofluorescence confocal images for protein subc...

Existing Uses

- 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

Discouraged Uses

- Name
    License-restricted use
  Description
    - Commercial use is prohibited under CC BY-NC-SA 4.0.

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 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.

📤

## Distribution

How will the dataset be distributed?

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

## Maintenance

How will the dataset be maintained?

Version
1.4
Updates

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