Guidelines for reproducible analysis of adaptive immune receptor repertoire sequencing data

  • Ayelet Peres
  • , Vered Klein
  • , Boaz Frankel
  • , William Lees
  • , Pazit Polak
  • , Mark Meehan
  • , Artur Rocha
  • , João Correia Lopes
  • , Gur Yaari

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Enhancing the reproducibility and comprehension of adaptive immune receptor repertoire sequencing (AIRR-seq) data analysis is critical for scientific progress. This study presents guidelines for reproducible AIRR-seq data analysis, and a collection of ready-to-use pipelines with comprehensive documentation. To this end, ten common pipelines were implemented using ViaFoundry, a user-friendly interface for pipeline management and automation. This is accompanied by versioned containers, documentation and archiving capabilities. The automation of pre-processing analysis steps and the ability to modify pipeline parameters according to specific research needs are emphasized. AIRR-seq data analysis is highly sensitive to varying parameters and setups; using the guidelines presented here, the ability to reproduce previously published results is demonstrated. This work promotes transparency, reproducibility, and collaboration in AIRR-seq data analysis, serving as a model for handling and documenting bioinformatics pipelines in other research domains.

Original languageEnglish
Article numberbbae221
JournalBriefings in Bioinformatics
Volume25
Issue number3
DOIs
StatePublished - 27 Mar 2024

Bibliographical note

Publisher Copyright:
© 2024 The Author(s). Published by Oxford University Press.

Keywords

  • AIRR-seq
  • FAIR
  • annotation
  • pipelines
  • preprocessing
  • reproducibility

Fingerprint

Dive into the research topics of 'Guidelines for reproducible analysis of adaptive immune receptor repertoire sequencing data'. Together they form a unique fingerprint.

Cite this