Evidence map›Paper›PMID 39460943›Full record

ArticleBioinformatics (Oxford, England)2024

Collapsible tree: interactive web app to present collapsible hierarchies.

Yuan Gao, Rob Patro, Peng Jiang

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Bioinformatics advances · 2026
    Article
  2. Article
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

3 authors.

Yuan GaoCancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States.
Rob PatroCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, United States.ORCID 0000-0001-8463-1675
Peng JiangCancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States.ORCID 0000-0002-7828-5486

Funding

A Modular Framework for Accurate, Interpretable, and Reproducible Analysis of Long Read RNA-Seq DataR01HG009937 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Michael Isaiah Love, Robert Patro · 2018 to 2026
$2.8M
National Science Foundation CCF-1750472NCI NIH HHSNHGRI NIH HHS R01 HG009937NIH HHS
6 · The paper itself

Abstract

motivationA crucial component of intuitive data visualization is presenting a hierarchical tree structure with interactive functions. For example, single-cell transcriptomics studies may generate gene expression values with developmental trajectories or cell lineage structures. Two common visualization methods, t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP), require two separate figures to depict the distribution of cell types and gene expression data, with low-dimension projections that may not capture the hierarchical structures among cells.

resultsHere, we present a JavaScript framework and an interactive web app named Collapsible Tree, which presents values jointly with interactive, expandable, and collapsible lineage structures. For example, the Collapsible Tree presents cellular states and gene expression from single-cell transcriptomics within a single hierarchical plot, enabling comparisons of gene expression across lineages and subtle patterns between sub-lineages. Our framework can facilitate the exploration of complicated value patterns that are not evident in UMAP or t-SNE plots. AVAILABILITY AND IMPLEMENTATION: The Collapsible Tree web interface is available at https://collapsibletree.data2in.net. The JavaScript library source code is available at https://github.com/data2intelligence/collapsible_tree.

Indexed as

SoftwareAlgorithmsCell LineageComputational BiologyGene Expression ProfilingHumansInternetSingle-Cell AnalysisTranscriptome

Identifiers

PMID39460943
PMCPMC11543613

What OpenQuestion holds

Textmetadata
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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.