Evidence map›Paper›PMID 34145435›Full record

ReviewNature reviews. Genetics2021

Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics.

Sophia K Longo, Margaret G Guo, Andrew L Ji, Paul A Khavari

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 641 papers.

0numbers the graph read from it
0cells of the map it votes in
641citing 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

641 citing papers in PubMed.

  1. Review
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  9. GPCR heteromers: Beyond the monomeric paradigm in neuropsychiatric drug discovery.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
    Review
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581 more citing papers are in PubMed but not listed here.

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.

Sophia K LongoProgram in Epithelial Biology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-1644-2738
Margaret G GuoProgram in Epithelial Biology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-7713-3846
Andrew L JiProgram in Epithelial Biology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-9688-5680
Paul A KhavariProgram in Epithelial Biology, Stanford University, Stanford, CA, USA. khavari@stanford.edu.ORCID http://orcid.org/0000-0003-0098-4989

Funding

Mechanisms of Epidermal Homeostasis and Early NeoplasiaR01AR043799 · NIAMS · STANFORD UNIVERSITY · PI PAUL KHAVARI · 1998 to 2026
$9.1M
Signaling Regulators of Epithelial Homeostasis and NeoplasiaR01AR049737 · NIAMS · STANFORD UNIVERSITY · PI PAUL KHAVARI · 2004 to 2026
$7.1M
Regulatory Variants in HUMAN SKIN DISEASESR01AR076965 · NIAMS · STANFORD UNIVERSITY · PI PAUL KHAVARI · 2020 to 2026
$3.6M
Regulators of TumorigenesisR01CA142635 · NCI · STANFORD UNIVERSITY · PI KHAVARI, PAUL · 2011 to 2020
$3.5M
NCI NIH HHS R01 CA142635NIAMS NIH HHS R01 AR043799NIAMS NIH HHS R01 AR049737NIAMS NIH HHS R01 AR076965
6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but does not capture their spatial distribution nor reveal local networks of intercellular communication acting in situ. A suite of recently developed techniques that localize RNA within tissue, including multiplexed in situ hybridization and in situ sequencing (here defined as high-plex RNA imaging) and spatial barcoding, can help address this issue. However, no method currently provides as complete a scope of the transcriptome as does scRNA-seq, underscoring the need for approaches to integrate single-cell and spatial data. Here, we review efforts to integrate scRNA-seq with spatial transcriptomics, including emerging integrative computational methods, and propose ways to effectively combine current methodologies.

Indexed as

Cell CommunicationSoftwareTranscriptomeAnimalsComputational BiologyHumansSequence Analysis, RNASingle-Cell Analysis

Identifiers

PMID34145435
PMCPMC9888017

What OpenQuestion holds

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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.