Evidence map›Paper›PMID 39005315›Full record

ArticlebioRxiv : the preprint server for biology2024

spatialGE: A user-friendly web application to democratize spatial transcriptomics analysis.

Oscar E Ospina, Roberto Manjarres-Betancur, Guillermo Gonzalez-Calderon, Alex C Soupir, Inna Smalley, Kenneth Tsai, Joseph Markowitz, Ethan Vallebuona, Anders Berglund, Steven Eschrich and 2 more

Abstract readPreprint
PubMed Full text at PMC Publisher
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

12 authors.

Oscar E OspinaDepartment of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0001-5986-4207
Roberto Manjarres-BetancurBiostatistics and Bioinformatics Shared Resource, Moffitt Cancer Center, Tampa, FL, USA.
Guillermo Gonzalez-CalderonBiostatistics and Bioinformatics Shared Resource, Moffitt Cancer Center, Tampa, FL, USA.
Alex C SoupirDepartment of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0003-1251-9179
Inna SmalleyDepartment of Metabolism and Physiology, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0002-6796-9145
Kenneth TsaiDepartment of Pathology, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0001-5325-212X
Joseph MarkowitzDepartment of Cutaneous Oncology, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0003-2490-5464
Ethan VallebuonaDepartment of Metabolism and Physiology, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0002-3153-9119
Anders BerglundDepartment of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0002-0393-3530
Steven EschrichDepartment of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0002-9833-2788
Xiaoqing YuDepartment of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA.ORCID 0000-0003-4585-9372
Brooke L FridleyDivision of Health Services and Outcomes Research, Children's Mercy, Kansas City, MO, USA.ORCID 0000-0001-7739-7956

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI John L. Cleveland · 1998 to 2026
$93.5M
Analytical tools for studying the tumor microenvironment leveraging spatial transcriptomicsU01CA274489 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI FRIDLEY, BROOKE L, YU, XIAOQING · 2022 to 2024
$1.2M
NCI NIH HHS P30 CA076292NCI NIH HHS U01 CA274489
6 · The paper itself

Abstract

Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, its potential is often underutilized due to the advanced data analysis and programming skills required. To address this, we present spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provides a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enables comparative analysis among samples and supports various ST technologies. We demonstrate the utility of spatialGE through its application in studying the tumor microenvironment of melanoma brain metastasis and Merkel cell carcinoma. Our results highlight the ability of spatialGE to identify spatial gene expression patterns and enrichments, providing valuable insights into the tumor microenvironment and its utility in democratizing ST data analysis for the wider scientific community.

Indexed as

bioinformaticsdata visualizationSpatial biologyspatial transcriptomicsstatistical analysistumor microenvironment

Identifiers

PMID39005315
PMCPMC11244876

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.