Evidence map›Paper›PMID 36864178›Full record

ReviewNature reviews. Genetics2023

Methods and applications for single-cell and spatial multi-omics.

Katy Vandereyken, Alejandro Sifrim, Bernard Thienpont, Thierry Voet

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 726 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
726citing papers in PubMed, 3 pooled it
–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

726 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Single-cell RNA sequencing offers novel perspectives in viral infection research.Frontiers in cellular and infection microbiology · 2026
    Pooled it
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  19. PEBP1 Regulates Ferroptosis in Acute Glaucoma: Targeted Therapy Using Engineered Exosomes.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
  20. Article

666 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.

Katy Vandereyken *KU Leuven Institute for Single Cell Omics (LISCO), University of Leuven, KU Leuven, Leuven, Belgium.
Alejandro Sifrim *KU Leuven Institute for Single Cell Omics (LISCO), University of Leuven, KU Leuven, Leuven, Belgium.
Bernard Thienpont *KU Leuven Institute for Single Cell Omics (LISCO), University of Leuven, KU Leuven, Leuven, Belgium.ORCID 0000-0002-8772-6845
Thierry VoetKU Leuven Institute for Single Cell Omics (LISCO), University of Leuven, KU Leuven, Leuven, Belgium. thierry.voet@kuleuven.be.ORCID 0000-0003-1204-9963

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future.

Indexed as

GenomeMultiomicsMetabolomeProteomeSingle-Cell AnalysisTranscriptomeProteome

Identifiers

PMID36864178
PMCPMC9979144

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.