Evidence map›Paper›PMID 33106757›Full record

ReviewComputational and structural biotechnology journal2020

Probing infectious disease by single-cell RNA sequencing: Progresses and perspectives.

Geyang Luo, Qian Gao, Shuye Zhang, Bo Yan

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. A granulin-positive macrophage subtype in mycobacterial granulomas alleviates tissue damage by limiting excessive inflammation.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. The CD38Frontiers in immunology · 2025
    Article
  12. [Revealing research progress for immunological characteristics of chronic hepatitis B applying single-cell RNA sequencing technology].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2024
    Review
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Review
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.

Geyang LuoShanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Qian GaoShanghai Public Health Clinical Center and Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Medical College and School of Basic Medical Sciences, Fudan University, Shanghai, China.
Shuye ZhangShanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Bo YanShanghai Public Health Clinical Center, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing application of single-cell RNA sequencing (scRNA-seq) technology in life science and biomedical research has significantly increased our understanding of the cellular heterogeneities in immunology, oncology and developmental biology. This review will summarize the development of various scRNA-seq technologies; primarily discussing the application of scRNA-seq on infectious diseases, and exploring the current development, challenges, and potential applications of scRNA-seq technology in the future.

Indexed as

3C, Chromosome Conformation CaptureACE2, Angiotensin-Converting Enzyme 2ARDS, acute respiratory distress syndromeATAC-seq, Assay for Transposase-Accessible Chromatin using sequencingBCR, B cell receptorCEL-seq, Cell Expression by Linear amplification and SequencingCLU, clusterinCOVID-19, corona virus disease 2019CRISPR, Clustered Regularly Interspaced Short Palindromic RepeatsCytoSeq, gene expression cytometryDENV, dengue virusFACS, fluorescence-activated cell sortingGNLY, granulysinGO analysis, Gene Ontology analysisHIV, Human Immunodeficiency VirusIAV, Influenza A virusIGHV/HD/HJ/HC, Immune globulin heavy V/D/J/C/ regionIGLV/LJ/LC, Immune globulin light V/J/C/ regionILC, Innate Lymphoid CellInfectious diseasesLIGER, Linked Inference of Genomics Experimental RelationshipsMAGIC, Markov Affinity-based Graph Imputation of CellsMARS-seq, Massively parallel single-cell RNA sequencingMATCHER, Manifold Alignment To CHaracterize Experimental RelationshipsMCMV, mouse cytomegalovirusmcSCRB-seq, molecular crowding single-cell RNA barcoding and sequencingMERFISH, Multiplexed, Error Robust Fluorescent In Situ HybridizationMLV, Moloney Murine Leukemia VirusMOFA, Multi-Omics Factor AnalysisMOI, multiplicity of infectionPBMCs, peripheral blood mononuclear cellspDCs, plasmacytoid dendritic cellsPLAC8, placenta-associated 8SARS-CoV-2, severe acute respiratory syndrome coronavirus 2SAVER, Single-cell Analysis Via Expression Recoverysci-RNA-seq, single-cell combinatorial indexing RNA sequencingscRNA-seq, single cell RNA sequencing technologyseqFISH, sequential Fluorescent In Situ HybridizationSingle-cell RNA sequencingsmart-seq, switching mechanism at 5′ end of the RNA transcript sequencingSPLit-seq, split pool ligation-based tranome sequencingSTARTRAC, Single T-cell Analysis by RNA sequencing and TCR TRACkingSTRT-seq, Single-cell Tagged Reverse Transcription sequencingTCR, T cell receptorTSLP, thymic stromal lymphopoietint-SNE, t-Distributed stochastic neighbor embeddingUMAP, Uniform Manifold Approximation and ProjectionUMI, Unique Molecular Identifier

Identifiers

PMID33106757
PMCPMC7577221

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.