Evidence map›Paper›PMID 40949989›Full record

ArticlebioRxiv : the preprint server for biology2025

shinyUMAP: an online tool for promoting understanding of single cell omics data visualization.

Rohan Misra, Kevin O'Leary, Wenna Chen, Deyou Zheng

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

4 authors.

Rohan MisraDepartment of Genetics, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, New York, USA.ORCID 0000-0002-6355-2764
Kevin O'LearyDepartment of Genetics, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, New York, USA.ORCID 0000-0001-7120-0550
Wenna ChenDepartment of Genetics, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, New York, USA.ORCID 0009-0005-1866-1477
Deyou ZhengDepartment of Genetics, Albert Einstein College of Medicine, 1300 Morris Park Ave., Bronx, New York, USA.ORCID 0000-0003-4354-5337

Funding

Cell fate choices by Tbx1 in forming the mammalian heartR01HL153920 · NHLBI · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI BERNICE E MORROW, Deyou Zheng · 2020 to 2026
$4.0M
Molecular pathogenesis of congenital heart disease mediated by neural crest and second heart field cellsR01HL163667 · NHLBI · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI MORROW, BERNICE E, ZHENG, DEYOU · 2022 to 2025
$2.5M
NHLBI NIH HHS R01 HL153920NHLBI NIH HHS R01 HL163667
6 · The paper itself

Abstract

Visualization is widely used to help explore and interpret high dimensional single cell (sc) omics data, such as scRNA-seq expression data. In particular, uniform manifold approximation and projection (UMAP) has become nearly ubiquitous in scientific publications that apply single cell omics technologies. Some experts have expressed concerns that the global cell-cell relationship, especially the spatial distances among cell clusters in a dataset, may not be faithfully depicted in a 2-dimensional (2D) UMAP. To help users to better appreciate this issue with their own data, we created an online server for the community to upload their single cell data and interactively make UMAPs with different hyper-parameters to witness how the distribution of cell clusters changes. The server thus can help promote proper usages of UMAP, especially to avoid the common pitfalls in misinterpretation of inter-cluster relationships in single cell studies.

Identifiers

PMID40949989
PMCPMC12424631

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.