Evidence map›Paper›PMID 26589402›Full record

ReviewGenome medicine2015

Practical guidelines for B-cell receptor repertoire sequencing analysis.

Gur Yaari, Steven H Kleinstein

Abstract readReview
In one paragraph

Review in Genome medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 156 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
156citing 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.

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

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

  1. Pooled it
  2. Article
  3. Article
  4. Humoral immunity in cancer.Signal transduction and targeted therapy · 2026
    Review
  5. Article
  6. Article
  7. AI-Driven BCR Modeling for Precision Immunology.International journal of molecular sciences · 2026
    Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Is the vaccination-induced B cell receptor repertoire predictable?Immunoinformatics (Amsterdam, Netherlands) · 2025
    Article
  20. Article

96 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

2 authors.

Gur YaariBioengineering Program, Faculty of Engineering, Bar-Ilan University, 5290002, Ramat Gan, Israel. gur.yaari@biu.ac.il.
Steven H KleinsteinInterdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06511, USA. steven.kleinstein@yale.edu.

Funding

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 AI104739NIAID NIH HHS R01AI104739
6 · The paper itself

Abstract

High-throughput sequencing of B-cell immunoglobulin repertoires is increasingly being applied to gain insights into the adaptive immune response in healthy individuals and in those with a wide range of diseases. Recent applications include the study of autoimmunity, infection, allergy, cancer and aging. As sequencing technologies continue to improve, these repertoire sequencing experiments are producing ever larger datasets, with tens- to hundreds-of-millions of sequences. These data require specialized bioinformatics pipelines to be analyzed effectively. Numerous methods and tools have been developed to handle different steps of the analysis, and integrated software suites have recently been made available. However, the field has yet to converge on a standard pipeline for data processing and analysis. Common file formats for data sharing are also lacking. Here we provide a set of practical guidelines for B-cell receptor repertoire sequencing analysis, starting from raw sequencing reads and proceeding through pre-processing, determination of population structure, and analysis of repertoire properties. These include methods for unique molecular identifiers and sequencing error correction, V(D)J assignment and detection of novel alleles, clonal assignment, lineage tree construction, somatic hypermutation modeling, selection analysis, and analysis of stereotyped or convergent responses. The guidelines presented here highlight the major steps involved in the analysis of B-cell repertoire sequencing data, along with recommendations on how to avoid common pitfalls.

Indexed as

Computational BiologyGuidelines as TopicHigh-Throughput Nucleotide SequencingHumansReceptors, Antigen, B-CellSequence AnalysisReceptors, Antigen, B-Cell

Identifiers

PMID26589402
PMCPMC4654805

What OpenQuestion holds

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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 OpenQuestion graph.