Evidence map›Paper›PMID 39130195›Full record

ArticleArXiv2024

Integrating spatially-resolved transcriptomics data across tissues and individuals: challenges and opportunities.

Boyi Guo, Wodan Ling, Sang Ho Kwon, Pratibha Panwar, Shila Ghazanfar, Keri Martinowich, Stephanie C Hicks

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 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

7 authors.

Boyi GuoDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0003-2950-2349
Wodan LingDivision of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, NY, USA.ORCID 0000-0001-7196-8543
Sang Ho KwonLieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.ORCID 0000-0001-5328-0956
Pratibha PanwarSchool of Mathematics and Statistics, The University of Sydney, NSW 2006, Australia.ORCID 0000-0002-7437-7084
Shila GhazanfarSchool of Mathematics and Statistics, The University of Sydney, NSW 2006, Australia.ORCID 0000-0001-7861-6997
Keri MartinowichLieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.ORCID 0000-0002-5237-0789
Stephanie C HicksDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-7858-0231

Funding

Laminar dissection of cortical human brain gene expression in neuropsychiatric disordersR01MH126393 · NIMH · LIEBER INSTITUTE, INC. · PI MARTINOWICH, KERI · 2021 to 2025
$3.9M
Statistical Methods for Enhanced Mapping of Microbiome RelationshipsR01GM151301 · NIGMS · FRED HUTCHINSON CANCER CENTER · PI MICHAEL Chiao-An WU · 2023 to 2026
$1.2M
NIGMS NIH HHS R01 GM151301NIMH NIH HHS R01 MH126393
6 · The paper itself

Abstract

Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. As the cost of generating these data decreases, these technologies provide an exciting opportunity to create large-scale atlases that integrate SRT data across multiple tissues, individuals, species, or phenotypes to perform population-level analyses. Here, we describe unique challenges of varying spatial resolutions in SRT data, as well as highlight the opportunities for standardized preprocessing methods along with computational algorithms amenable to atlas-scale datasets leading to improved sensitivity and reproducibility in the future.

Indexed as

integrative analysismulti-samplepopulation-levelspatial alignmentSpatially-resolved transcriptomicsspatial registration

Identifiers

PMID39130195
PMCPMC11312629

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.