Evidence map›Paper›PMID 40501593›Full record

ArticlebioRxiv : the preprint server for biology2025

scExploreR: a flexible platform for democratized analysis of multimodal single-cell data by non-programmers.

William M Showers, Jairav Desai, Stephanie R Gipson, Krysta L Engel, Clayton Smith, Craig T Jordan, Austin E Gillen

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

William M ShowersDivision of Hematology, University of Colorado School of Medicine, Aurora, CO, USA.ORCID 0000-0001-5989-8570
Jairav DesaiRefinedScience, Aurora, Colorado, USA.
Stephanie R GipsonDivision of Hematology, University of Colorado School of Medicine, Aurora, CO, USA.ORCID 0009-0003-0352-6251
Krysta L EngelDivision of Hematology, University of Colorado School of Medicine, Aurora, CO, USA.ORCID 0000-0003-3132-1491
Clayton SmithDivision of Hematology, University of Colorado School of Medicine, Aurora, CO, USA.
Craig T JordanDivision of Hematology, University of Colorado School of Medicine, Aurora, CO, USA.ORCID 0000-0003-0869-3465
Austin E GillenDivision of Hematology, University of Colorado School of Medicine, Aurora, CO, USA.ORCID 0000-0003-2928-6308

Funding

Therapeutic Targeting of Human AML Stem CellsR35CA242376 · NCI · UNIVERSITY OF COLORADO DENVER · PI Craig T. Jordan · 2020 to 2026
$5.6M
BLRD VA IK2 BX004952NCI NIH HHS R35 CA242376
6 · The paper itself

Abstract

Single-cell sequencing has revolutionized biomedical research by uncovering cellular heterogeneity in disease mechanisms, with significant potential for advancing personalized medicine. However, participation in single-cell data analysis is limited by the programming experience required to access data. Several existing browsers allow the interrogation of single-cell data through a point-and-click interface accessible to non-programmers, but many of these browsers are limited in the depth of analysis that can be performed, or the flexibility of input data formats accepted. Thus, programming experience is still required for comprehensive data analysis. We developed scExploreR to address these limitations and extend the range of analysis tasks that can be performed by non-programmers. scExploreR is implemented as a packaged R Shiny app that can be run locally or easily deployed for multiple users on a server. scExploreR offers extensive customization options for plots, allowing users to generate publication quality figures. Leveraging our SCUBA package, scExploreR seamlessly handles multimodal data, providing identical plotting capabilities regardless of input format. By empowering researchers to directly explore and analyze single-cell data, scExploreR bridges communication gaps between biological and computational scientists, streamlining insight generation.

Indexed as

CITE-seqSeuratshinyappSingle-cell RNA-seq

Identifiers

PMID40501593
PMCPMC12154577

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.