Evidence map›Paper›PMID 39117696›Full record

ArticleScientific reports2024

High-throughput image processing software for the study of nuclear architecture and gene expression.

Adib Keikhosravi, Faisal Almansour, Christopher H Bohrer, Nadezda A Fursova, Krishnendu Guin, Varun Sood, Tom Misteli, Daniel R Larson, Gianluca Pegoraro

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Re-establishment of TAD boundary organization during DNA replication.bioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. TAD boundaries and gene activity are uncoupled.bioRxiv : the preprint server for biology · 2026
    Article
  8. Article
  9. Article
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  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Adib KeikhosraviHigh-Throughput Imaging Facility, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA.
Faisal Almansour *Cell Biology of Genomes, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA.
Christopher H BohrerSystem Biology of Gene Expression, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA.
Nadezda A FursovaSystem Biology of Gene Expression, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA.
Krishnendu Guin *Cell Biology of Genomes, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA.
Varun Sood *Cell Biology of Genomes, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA.
Tom MisteliCell Biology of Genomes, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA.
Daniel R LarsonSystem Biology of Gene Expression, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA.
Gianluca PegoraroHigh-Throughput Imaging Facility, National Cancer Institute, National Institute of Health, Bethesda, MD, 20892, USA. gianluca.pegoraro@nih.gov.

Funding

Nuclear Architecture and DiseaseZIABC010309 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI MISTELI, THOMAS A · 2009 to 2025
$39.8M
Transcription Dynamics in Single CellsZIABC011383 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI LARSON, DANIEL · 2011 to 2025
$23.8M
HiTIF Microscopy Core FacilityZICBC011567 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI PEGORARO, GIANLUCA · 2014 to 2025
$15.8M
Intramural NIH HHS ZIA BC010309Intramural NIH HHS ZIA BC011383Intramural NIH HHS ZIC BC011567NIH HHS 1-ZIA-BC010309-24NIH HHS 1-ZIA-BC011383-12NIH HHS 1-ZIC-BC011567-09
6 · The paper itself

Abstract

High-throughput imaging (HTI) generates complex imaging datasets from a large number of experimental perturbations. Commercial HTI software programs for image analysis workflows typically do not allow full customization and adoption of new image processing algorithms in the analysis modules. While open-source HTI analysis platforms provide individual modules in the workflow, like nuclei segmentation, spot detection, or cell tracking, they are often limited in integrating novel analysis modules or algorithms. Here, we introduce the High-Throughput Image Processing Software (HiTIPS) to expand the range and customization of existing HTI analysis capabilities. HiTIPS incorporates advanced image processing and machine learning algorithms for automated cell and nuclei segmentation, spot signal detection, nucleus tracking, nucleus registration, spot tracking, and quantification of spot signal intensity. Furthermore, HiTIPS features a graphical user interface that is open to integration of new analysis modules for existing analysis pipelines and to adding new analysis modules. To demonstrate the utility of HiTIPS, we present three examples of image analysis workflows for high-throughput DNA FISH, immunofluorescence (IF), and live-cell imaging of transcription in single cells. Altogether, we demonstrate that HiTIPS is a user-friendly, flexible, and open-source HTI software platform for a variety of cell biology applications.

Indexed as

Cell NucleusImage Processing, Computer-AssistedSoftwareAlgorithmsGene ExpressionHumansIn Situ Hybridization, FluorescenceMachine Learning

Identifiers

PMID39117696
PMCPMC11310328

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Registered trials

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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.