Evidence map›Paper›PMID 38895230›Full record

ArticlebioRxiv : the preprint server for biology2024

Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACIT.

Khoa L A Huynh, Katarzyna M Tyc, Bruno F Matuck, Quinn T Easter, Aditya Pratapa, Nikhil V Kumar, Paola Pérez, Rachel Kulchar, Thomas Pranzatelli, Deiziane de Souza and 11 more

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In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors.

Khoa L A HuynhDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Katarzyna M TycDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Bruno F MatuckLab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA.
Quinn T EasterLab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA.
Aditya PratapaDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
Nikhil V KumarLab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA.
Paola PérezSalivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA.
Rachel KulcharSalivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA.
Thomas PranzatelliAdeno-Associated Virus Biology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA.
Deiziane de SouzaDepartment of Pathology, Medicine School of University of Sao Paulo, SP, BR.
Theresa M WeaverLab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA.
Xufeng QuMassey Cancer Center, Richmond VA, USA.
Luiz Alberto Valente SoaresDivision of Dentistry of Hospital das Clinicas of University of Sao Paulo, SP, BR.
Marisa DolhnokoffDepartment of Pathology, Medicine School of University of Sao Paulo, SP, BR.
David E KleinerLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Stephen M HewittLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Luiz Fernando Ferraz da SilvaDepartment of Pathology, Medicine School of University of Sao Paulo, SP, BR.
Vanderson Geraldo RochaDepartment of Hematology, Transfusion and Cell Therapy Service, University of Sao Paulo, Sao Paulo, Brazil.
Blake M WarnerSalivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA.
Kevin M ByrdLab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, MD, USA.
Jinze LiuDepartment of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.

Funding

Virus Vector Shared ResourceP30CA016059 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI Kim Felder Rhoads · 1985 to 2026
$51.0M
Wright Regional Center for Clinical and Translational ScienceUM1TR004360 · NCATS · VIRGINIA COMMONWEALTH UNIVERSITY · PI FREDERICK Gerard MOELLER · 2023 to 2026
$16.3M
Postmortem PathologyZICBC010685 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI KLEINER, DAVID ERWIN · 2009 to 2025
$14.3M
NCATS NIH HHS UM1 TR004360NCI NIH HHS P30 CA016059
6 · The paper itself

Abstract

Identifying cell types and states remains a time-consuming and error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data, using unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integration of TACIT-identified cell with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discover under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

Indexed as

artificial intelligencebraincell typingdeep learningfluorescence microscopyintestinemachine learningmultimodalmultiplex imagingproteomicssalivary glandsingle cell analysisspatial biologyspatial multiomicstranscriptomics

Identifiers

PMID38895230
PMCPMC11185514

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.