Evidence map›Paper›PMID 37789738›Full record

ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2023

Assessing the performance of the Cell Painting assay across different imaging systems.

Callum Tromans-Coia, Nasim Jamali, Hamdah Shafqat Abbasi, Kenneth A Giuliano, Mai Hagimoto, Kevin Jan, Erika Kaneko, Stefan Letzsch, Alexander Schreiner, Jonathan Z Sexton and 7 more

Abstract read
In one paragraph

Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
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  5. Alternate dyes for image-based profiling assays.SLAS discovery : advancing life sciences R & D · 2025
    Article
  6. Prediction of Bioactive Metabolites from AmericanJournal of natural products · 2025
    Article
  7. Article
  8. Article
  9. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Callum Tromans-CoiaDepartment: Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.ORCID 0000-0002-5518-8915
Nasim JamaliDepartment: Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Hamdah Shafqat AbbasiDepartment: Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Kenneth A GiulianoNikon Instruments Inc., Melville, New York, USA.
Mai HagimotoYokogawa Electric Corporation, Kanazawa, Ishikawa, Japan.
Kevin JanYokogawa Corporation of America, Newnan, Georgia, USA.
Erika KanekoYokogawa Electric Corporation, Kanazawa, Ishikawa, Japan.
Stefan LetzschRevvity, Inc., Waltham, Massachusetts, USA.
Alexander SchreinerRevvity, Inc., Waltham, Massachusetts, USA.
Jonathan Z SextonDepartment of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA.
Mahomi SuzukiYokogawa Electric Corporation, Kanazawa, Ishikawa, Japan.
O Joseph TraskRevvity, Inc., Waltham, Massachusetts, USA.
Mitsunari YamaguchiYokogawa Electric Corporation, Kanazawa, Ishikawa, Japan.
Fumiki YanagawaNikon Instruments Inc., Melville, New York, USA.
Michael YangNikon Instruments Inc., Melville, New York, USA.
Anne E CarpenterDepartment: Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.ORCID 0000-0003-1555-8261
Beth A CiminiDepartment: Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.ORCID 0000-0001-9640-9318

Funding

Extracting rich information from biological imagesR35GM122547 · NIGMS · BROAD INSTITUTE, INC. · PI Anne E. Carpenter · 2017 to 2026
$6.2M
NIGMS NIH HHS R35 GM122547
6 · The paper itself

Abstract

Quantitative microscopy is a powerful method for performing phenotypic screens from which image-based profiling can extract a wealth of information, termed profiles. These profiles can be used to elucidate the changes in cellular phenotypes across cell populations from different patient samples or following genetic or chemical perturbations. One such image-based profiling method is the Cell Painting assay, which provides morphological insight through the imaging of eight cellular compartments. Here, we examine the performance of the Cell Painting assay across multiple high-throughput microscope systems and find that all are compatible with this assay. Furthermore, we determine independently for each microscope system the best performing settings, providing those who wish to adopt this assay an ideal starting point for their own assays. We also explore the impact of microscopy setting changes in the Cell Painting assay and find that few dramatically reduce the quality of a Cell Painting profile, regardless of the microscope used.

Indexed as

Biological AssayMicroscopyHumansCell Paintingimage-based profilingphenotypic screeningquantitative imaging

Identifiers

PMID37789738
PMCPMC10841730

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.