Evidence map›Paper›PMID 30726743›Full record

ArticleCell reports2019

RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types.

Gianni Monaco, Bernett Lee, Weili Xu, Seri Mustafah, You Yi Hwang, Christophe Carré, Nicolas Burdin, Lucian Visan, Michele Ceccarelli, Michael Poidinger and 3 more

Registry-linked trialAbstract read
In one paragraph

Article in Cell reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04570306 (Whole Blood Transcriptional and Mass Cytometry Immune Profiling in Systemic Lupus Erythematosus), which is not on this map. Cited by 629 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
629citing papers in PubMed, 1 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.

NCT04570306 completednot on this mapstarted 2020, after this paper: background citation

Whole Blood Transcriptional and Mass Cytometry Immune Profiling in Systemic Lupus Erythematosus (SLE) Patients to Discern the Salutary Effects of Belimumab on Halting Disease Progression and Flares Without Compromising Host Fitness

TypeobservationalSponsorBiomedical Research Foundation, Academy of AthensRan2020 to 2023Enrolled85ConditionsSystemic Lupus ErythematosusArmsBelimumab
3 · Its place in the literature

Who cites it

629 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Decoding B-cell Signatures of Complete Pathologic Response to Perioperative Chemoimmunotherapy in Non-Small Cell Lung Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
    Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Priming of Multiple HIV Neutralizing B Cell Precursors in Humans.medRxiv : the preprint server for health sciences · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

569 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

13 authors.

Gianni MonacoSingapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore; Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L78TX, UK; Department of Biomedicine, University Hospital and University of Basel, 4031 Basel, Switzerland. Electronic address: mongianni1@gmail.com.
Bernett LeeSingapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore.
Weili XuSingapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore.
Seri MustafahSingapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore.
You Yi HwangSingapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore.
Christophe CarréSanofi Pasteur, Marcy l'Etoile, France.
Nicolas BurdinSanofi Pasteur, Marcy l'Etoile, France.
Lucian VisanSanofi Pasteur, Marcy l'Etoile, France.
Michele CeccarelliBIOGEM Research Center, Ariano Irpino, Italy; Department of Science and Technology, University of Sannio, Benevento, Italy.
Michael PoidingerSingapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore.
Alfred ZippeliusDepartment of Biomedicine, University Hospital and University of Basel, 4031 Basel, Switzerland.
João Pedro de MagalhãesIntegrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L78TX, UK. Electronic address: jp@senescence.info.
Anis LarbiSingapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore; Department of Biology, Faculty of Sciences, University Tunis El Manar, Tunis, Tunisia; Faculty of Medicine, University of Sherbrooke, Sherbrooke, QC, Canada; Department of Microbiology, Immunology Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. Electronic address: anis_larbi@immunol.a-star.edu.sg.

Funding

Wellcome TrustWellcome Trust 208375/Z/17/Z
6 · The paper itself

Abstract

The molecular characterization of immune subsets is important for designing effective strategies to understand and treat diseases. We characterized 29 immune cell types within the peripheral blood mononuclear cell (PBMC) fraction of healthy donors using RNA-seq (RNA sequencing) and flow cytometry. Our dataset was used, first, to identify sets of genes that are specific, are co-expressed, and have housekeeping roles across the 29 cell types. Then, we examined differences in mRNA heterogeneity and mRNA abundance revealing cell type specificity. Last, we performed absolute deconvolution on a suitable set of immune cell types using transcriptomics signatures normalized by mRNA abundance. Absolute deconvolution is ready to use for PBMC transcriptomic data using our Shiny app (https://github.com/giannimonaco/ABIS). We benchmarked different deconvolution and normalization methods and validated the resources in independent cohorts. Our work has research, clinical, and diagnostic value by making it possible to effectively associate observations in bulk transcriptomics data to specific immune subsets.

Indexed as

TranscriptomeAdultBasophilsBenchmarkingB-LymphocytesCell LineageDendritic CellsFemaleFlow CytometryHealthy VolunteersHigh-Throughput Nucleotide SequencingHumansImmunophenotypingKiller Cells, NaturalMaleMonocytesRNA, Messengerdeconvolutionflow cytometrygene moduleshousekeepingimmune systemmRNA abundancemRNA compositionmRNA heterogeneityRNA-seqtranscriptome

Identifiers

PMID30726743
PMCPMC6367568

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.