Evidence map›Paper›PMID 34648021›Full record

ArticleNucleic acids research2022

scMRMA: single cell multiresolution marker-based annotation.

Jia Li, Quanhu Sheng, Yu Shyr, Qi Liu

Abstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. celltypeEnrich: a consensus-based scRNA-seq cluster annotation tool.bioRxiv : the preprint server for biology · 2026
    Article
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  5. Article
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  7. Mapping CMV-related immune signatures in blood, aorta and perivascular mediastinal adipose tissue.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
    Article
  8. Article
  9. Article
  10. CXCR4iScience · 2025
    Article
  11. Article
  12. Review
  13. Article
  14. Mapping Cell Identity from scRNA-seq: A primer on computational methods.Computational and structural biotechnology journal · 2025
    Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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.

Jia LiDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
Quanhu ShengDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
Yu ShyrDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
Qi LiuDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37203, USA.ORCID 0000-0001-8892-7078

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MATTHEW J TYSKA · 1995 to 2026
$172.8M
TISSUE CoreP50CA098131 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PARK, BEN HO, PIETENPOL, JENNIFER A · 2003 to 2024
$48.7M
Understanding and Controlling p120 Dysfunction in CRCP50CA095103 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI COFFEY, ROBERT J. · 2002 to 2017
$33.6M
Vanderbilt-Ingram Cancer Center SPORE in Gastrointestinal CancerP50CA236733 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI STEPHEN W. FESIK · 2019 to 2026
$19.6M
Molecular, Cellular and Tissue Characterization UnitU2CCA233291 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI COFFEY, ROBERT J., SHRUBSOLE, MARTHA J. · 2018 to 2023
$12.2M
Single-Cell Biology and Data Analysis Shared Resource (SCB-DA SR)U54CA217450 · NCI · VANDERBILT UNIVERSITY · PI WEAVER, ALISSA M · 2018 to 2022
$8.5M
NCI NIH HHS P30 CA068485NCI NIH HHS P50 CA095103NCI NIH HHS P50 CA098131NCI NIH HHS P50 CA236733NCI NIH HHS U2C CA233291NCI NIH HHS U54 CA217450
6 · The paper itself

Abstract

Single-cell RNA sequencing has become a powerful tool for identifying and characterizing cellular heterogeneity. One essential step to understanding cellular heterogeneity is determining cell identities. The widely used strategy predicts identities by projecting cells or cell clusters unidirectionally against a reference to find the best match. Here, we develop a bidirectional method, scMRMA, where a hierarchical reference guides iterative clustering and deep annotation with enhanced resolutions. Taking full advantage of the reference, scMRMA greatly improves the annotation accuracy. scMRMA achieved better performance than existing methods in four benchmark datasets and successfully revealed the expansion of CD8 T cell populations in squamous cell carcinoma after anti-PD-1 treatment.

Indexed as

BiomarkersSingle-Cell AnalysisSoftwareAlgorithmsCluster AnalysisComputational BiologyDatabases, GeneticGene Expression ProfilingHumansMolecular Sequence AnnotationReproducibility of ResultsSequence Analysis, RNABiomarkers

Identifiers

PMID34648021
PMCPMC8789072

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.