Evidence map›Paper›PMID 32574157›Full record

ArticlePLoS computational biology2020

Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data.

Nima Nouri, Steven H Kleinstein

Abstract read
In one paragraph

Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Comprehensive Mapping of Immune Nanobody Repertoires with NanoMAP.bioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Explore antibody repertoire in the era of AI.Acta biochimica et biophysica Sinica · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Computational detection of antigen-specific B cell receptors following immunization.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Evaluating methods for B-cell clonal family assignment.bioRxiv : the preprint server for biology · 2024
    Article
  17. Review
  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

2 authors.

Nima NouriDepartment of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America.ORCID 0000-0001-8348-5717
Steven H KleinsteinDepartment of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America.ORCID 0000-0003-4957-1544

Funding

MEDICAL INFORMATICS RESEARCH TRAINING AT YALET15LM007056 · NLM · YALE UNIVERSITY · PI Mark Bender Gerstein, LUCILA OHNO-MACHADO · 1987 to 2026
$22.2M
COMPUTATIONAL TOOLS FOR THE ANALYSIS OF HIGH-THROUGHPUT IMMUNOGLOBULIN SEQUENCING EXPERIMENTSR01AI104739 · NIAID · YALE UNIVERSITY · PI KLEINSTEIN, STEVEN H. · 2014 to 2022
$3.6M
NIAID NIH HHS R01 AI104739NLM NIH HHS T15 LM007056
6 · The paper itself

Abstract

Adaptive immune receptor repertoire sequencing (AIRR-Seq) offers the possibility of identifying and tracking B cell clonal expansions during adaptive immune responses. Members of a B cell clone are descended from a common ancestor and share the same initial V(D)J rearrangement, but their B cell receptor (BCR) sequence may differ due to the accumulation of somatic hypermutations (SHMs). Clonal relationships are learned from AIRR-seq data by analyzing the BCR sequence, with the most common methods focused on the highly diverse junction region. However, clonally related cells often share SHMs which have been accumulated during affinity maturation. Here, we investigate whether shared SHMs in the V and J segments of the BCR can be leveraged along with the junction sequence to improve the ability to identify clonally related sequences. We develop independent distance functions that capture junction similarity and shared mutations, and combine these in a spectral clustering framework to infer the BCR clonal relationships. Using both simulated and experimental data, we show that this model improves both the sensitivity and specificity for identifying B cell clones. Source code for this method is freely available in the SCOPer (Spectral Clustering for clOne Partitioning) R package (version 0.2 or newer) in the Immcantation framework: www.immcantation.org under the AGPLv3 license.

Indexed as

MutationB-LymphocytesComplementarity Determining RegionsComputational BiologyHigh-Throughput Nucleotide SequencingHumansReceptors, Antigen, B-CellRecombination, GeneticComplementarity Determining RegionsReceptors, Antigen, B-Cell

Identifiers

PMID32574157
PMCPMC7347241

What OpenQuestion holds

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Registered trials

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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.