Evidence map›Paper›PMID 38444087›Full record

ArticleBioinformatics (Oxford, England)2024

SpatialView: an interactive web application for visualization of multiple samples in spatial transcriptomics experiments.

Chitrasen Mohanty, Aman Prasad, Lingxin Cheng, Lisa M Arkin, Bridget E Shields, Beth Drolet, Christina Kendziorski

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Chitrasen MohantyDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53726, United States.ORCID 0009-0008-0864-6371
Aman PrasadDepartment of Dermatology, University of Pennsylvania, Philadelphia, PA 19104, United States.
Lingxin ChengDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53726, United States.
Lisa M ArkinDepartment of Dermatology, University of Wisconsin-Madison, Madison, WI 53715, United States.
Bridget E ShieldsDepartment of Dermatology, University of Wisconsin-Madison, Madison, WI 53715, United States.
Beth DroletDepartment of Dermatology, University of Wisconsin-Madison, Madison, WI 53715, United States.
Christina KendziorskiDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53726, United States.

Funding

Statistical methods for spatial RNA sequencing experimentsR01GM102756 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI KENDZIORSKI, CHRISTINA · 2012 to 2024
$3.8M
NIGMS NIH HHS R01 GM102756NIH HHS GM102756
6 · The paper itself

Abstract

motivationSpatial transcriptomics (ST) experiments provide spatially localized measurements of genome-wide gene expression allowing for an unprecedented opportunity to investigate cellular heterogeneity and organization within a tissue. Statistical and computational frameworks exist that implement robust methods for pre-processing and analyzing data in ST experiments. However, the lack of an interactive suite of tools for visualizing ST data and results currently limits the full potential of ST experiments.

resultsTo fill the gap, we developed SpatialView, an open-source web browser-based interactive application for visualizing data and results from multiple 10× Genomics Visium ST experiments. We anticipate SpatialView will be useful to a broad array of clinical and basic science investigators utilizing ST to study disease. AVAILABILITY AND IMPLEMENTATION: SpatialView is available at https://github.com/kendziorski-lab/SpatialView (and https://doi.org/10.5281/zenodo.10223907); a demo application is available at https://www.biostat.wisc.edu/˜kendzior/spatialviewdemo/.

Indexed as

GenomicsSoftwareGene Expression ProfilingGenomeWeb Browser

Identifiers

PMID38444087
PMCPMC10957517

What OpenQuestion holds

Textmetadata
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.