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Practical guidelines for B-cell receptor repertoire sequencing analysis.

Gur Yaari1, Steven H Kleinstein2,3

  • 1Bioengineering Program, Faculty of Engineering, Bar-Ilan University, 5290002, Ramat Gan, Israel. gur.yaari@biu.ac.il.

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Summary

Analyzing B-cell receptor repertoire sequencing data is complex. These guidelines offer practical steps for processing large datasets, from raw reads to repertoire properties, aiding adaptive immunity research.

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Area of Science:

  • Immunology
  • Bioinformatics
  • Genomics

Background:

  • High-throughput sequencing of B-cell immunoglobulin repertoires provides insights into adaptive immunity in health and disease.
  • Applications span autoimmunity, infection, allergy, cancer, and aging, generating massive datasets requiring specialized bioinformatics analysis.
  • Lack of standardized pipelines and data sharing formats hinders effective analysis.

Purpose of the Study:

  • To provide practical guidelines for B-cell receptor repertoire sequencing data analysis.
  • To cover the entire analytical workflow from raw sequencing reads to repertoire properties.
  • To address common pitfalls and promote standardization in the field.

Main Methods:

  • Detailed methods for pre-processing, including unique molecular identifier (UMI) and sequencing error correction.
  • V(D)J assignment, novel allele detection, and clonal assignment strategies.
  • Techniques for lineage tree construction, somatic hypermutation modeling, selection analysis, and stereotyped response identification.

Main Results:

  • A comprehensive set of guidelines for analyzing large-scale B-cell repertoire sequencing data.
  • Recommendations for various analytical steps, including error correction, V(D)J assignment, and clonal analysis.
  • Methods for assessing repertoire properties such as somatic hypermutation and selection.

Conclusions:

  • Standardized analysis pipelines are crucial for effectively interpreting large B-cell repertoire sequencing datasets.
  • These guidelines offer a practical framework to navigate the complexities of repertoire data analysis.
  • Adoption of these guidelines can improve reproducibility and comparability across studies of adaptive immunity.