Evidence map›Paper›PMID 36623812›Full record

ReviewJournal of pathology and translational medicine2023

Perspectives on single-nucleus RNA sequencing in different cell types and tissues.

Nayoung Kim, Huiram Kang, Areum Jo, Seung-Ah Yoo, Hae-Ock Lee

Abstract readReview
In one paragraph

Review in Journal of pathology and translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

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  16. Cross-assay RNA modeling reveals cancer biomarkers.bioRxiv : the preprint server for biology · 2026
    Article
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8 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

5 authors.

Nayoung KimDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Huiram KangDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Areum JoDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Seung-Ah YooDepartment of Biomedicine and Health Sciences, Graduate School, The Catholic University of Korea, Seoul, Korea.
Hae-Ock LeeDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea.

Funding

Ministry of Science and ICTNational Research Foundation of Korea 2019M3A9B6064691
6 · The paper itself

Abstract

Single-cell RNA sequencing has become a powerful and essential tool for delineating cellular diversity in normal tissues and alterations in disease states. For certain cell types and conditions, there are difficulties in isolating intact cells for transcriptome profiling due to their fragility, large size, tight interconnections, and other factors. Single-nucleus RNA sequencing (snRNA-seq) is an alternative or complementary approach for cells that are difficult to isolate. In this review, we will provide an overview of the experimental and analysis steps of snRNA-seq to understand the methods and characteristics of general and tissue-specific snRNA-seq data. Knowing the advantages and limitations of snRNA-seq will increase its use and improve the biological interpretation of the data generated using this technique.

Indexed as

RNA sequencingSingle-cell analysisTranscriptome

Identifiers

PMID36623812
PMCPMC9846005

What OpenQuestion holds

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LicenceCC BY-NC
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.