Evidence map›Paper›PMID 38151443›Full record

ReviewTrends in immunology2024

B cell phylogenetics in the single cell era.

Kenneth B Hoehn, Steven H Kleinstein

Open access · greenAbstract readReview
In one paragraph

Review in Trends in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
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

15 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. AI-Driven BCR Modeling for Precision Immunology.International journal of molecular sciences · 2026
    Review
  3. Explore antibody repertoire in the era of AI.Acta biochimica et biophysica Sinica · 2025
    Article
  4. Article
  5. Characterization of human CMV-specific CD8Cell reports methods · 2025
    Article
  6. Article
  7. Article
  8. Exact and efficient phylodynamic simulation from arbitrarily large populations.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. 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

2 authors at 2 institutions in 1 country.

Kenneth B HoehnDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA. Electronic address: kenneth.b.hoehn@dartmouth.edu.
Steven H KleinsteinDepartment of Pathology, Yale School of Medicine, New Haven, CT 06520, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520, USA.
Dartmouth College · USYale University · US

Funding

COMPUTATIONAL TOOLS FOR THE ANALYSIS OF HIGH-THROUGHPUT IMMUNOGLOBULIN SEQUENCING EXPERIMENTSR01AI104739 · NIAID · YALE UNIVERSITY · PI KLEINSTEIN, STEVEN H. · 2014 to 2022
$3.6M
Computational mapping of human B cell migration and differentiation pathwaysR00AI159302 · NIAID · DARTMOUTH COLLEGE · PI HOEHN, KENNETH · 2023 to 2024
$498k
NIAID NIH HHS R00 AI159302NIAID NIH HHS R01 AI104739
6 · The paper itself

Abstract

The widespread availability of single-cell RNA sequencing (scRNA-seq) has led to the development of new methods for understanding immune responses. Single-cell transcriptome data can now be paired with B cell receptor (BCR) sequences. However, RNA from BCRs cannot be analyzed like most other genes because BCRs are genetically diverse within individuals. In humans, BCRs are shaped through recombination followed by mutation and selection for antigen binding. As these processes co-occur with cell division, B cells can be studied using phylogenetic trees representing the mutations within a clone. B cell trees can link experimental timepoints, tissues, or cellular subtypes. Here, we review the current state and potential of how B cell phylogenetics can be combined with single-cell data to understand immune responses.

Indexed as

B-LymphocytesReceptors, Antigen, B-CellAdaptive ImmunityHumansMutationPhylogenyReceptors, Antigen, B-Celladaptive immunityB cellB cell receptorevolutionphylogeneticssingle cell

Identifiers

PMID38151443
PMCPMC10872299
OpenAlexW4390276275

What OpenQuestion holds

Textmetadata
LicenceTDM
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.