Evidence map›Paper›PMID 34017005›Full record

SynthesisNature communications2021

Interpretation of T cell states from single-cell transcriptomics data using reference atlases.

Massimo Andreatta, Jesus Corria-Osorio, Sören Müller, Rafael Cubas, George Coukos, Santiago J Carmona

Abstract readMeta-Analysis
In one paragraph

Synthesis in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 372 papers.

0numbers the graph read from it
0cells of the map it votes in
372citing 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

372 citing papers in PubMed.

  1. Trial
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  4. Immune dysregulation in the prostates of C57BL/6The Journal of pathology · 2026
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  7. Review
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  19. Integrated Single-Cell and TCR Profiling Reveals Protection-Associated CD8Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  20. Article

312 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

6 authors.

Massimo AndreattaDepartment of Oncology, Lausanne Branch, Ludwig Institute for Cancer Research, CHUV and University of Lausanne, Lausanne, Epalinges, Switzerland.ORCID 0000-0002-8036-2647
Jesus Corria-OsorioDepartment of Oncology, Lausanne Branch, Ludwig Institute for Cancer Research, CHUV and University of Lausanne, Lausanne, Epalinges, Switzerland.
Sören MüllerDepartment of Bioinformatics and Computational Biology, Genentech, South San Francisco, CA, USA.ORCID 0000-0001-9490-5270
Rafael CubasDepartment of Translational Oncology, Genentech, South San Francisco, CA, USA.
George CoukosDepartment of Oncology, Lausanne Branch, Ludwig Institute for Cancer Research, CHUV and University of Lausanne, Lausanne, Epalinges, Switzerland.ORCID 0000-0001-8813-7367
Santiago J CarmonaDepartment of Oncology, Lausanne Branch, Ludwig Institute for Cancer Research, CHUV and University of Lausanne, Lausanne, Epalinges, Switzerland. santiago.carmona@unil.ch.ORCID 0000-0002-2495-0671

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) has revealed an unprecedented degree of immune cell diversity. However, consistent definition of cell subtypes and cell states across studies and diseases remains a major challenge. Here we generate reference T cell atlases for cancer and viral infection by multi-study integration, and develop ProjecTILs, an algorithm for reference atlas projection. In contrast to other methods, ProjecTILs allows not only accurate embedding of new scRNA-seq data into a reference without altering its structure, but also characterizing previously unknown cell states that "deviate" from the reference. ProjecTILs accurately predicts the effects of cell perturbations and identifies gene programs that are altered in different conditions and tissues. A meta-analysis of tumor-infiltrating T cells from several cohorts reveals a strong conservation of T cell subtypes between human and mouse, providing a consistent basis to describe T cell heterogeneity across studies, diseases, and species.

Indexed as

AnimalsCell DifferentiationCohort StudiesDisease Models, AnimalGene Expression RegulationHumansLymphocytes, Tumor-InfiltratingMiceNeoplasmsReference ValuesRNA-SeqSingle-Cell AnalysisSoftwareSpecies SpecificityT-LymphocytesT-Lymphocyte Subsets

Identifiers

PMID34017005
PMCPMC8137700

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.