nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework

• Published in: PLoS computational biology Vol. 20; no. 7; p. e1012265
• Main Authors: Gabernet, Gisela, Marquez, Susanna, Bjornson, Robert, Peltzer, Alexander, Meng, Hailong, Aron, Edel, Lee, Noah Y., Jensen, Cole G., Ladd, David, Polster, Mark, Hanssen, Friederike, Heumos, Simon, Yaari, Gur, Kowarik, Markus C., Nahnsen, Sven, Kleinstein, Steven H.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 26.07.2024; Public Library of Science (PLoS)
• Subjects: Adaptive Immunity - genetics; B-Lymphocytes - immunology; Biology and Life Sciences; Cell receptors; Computational Biology - methods; COVID-19 - genetics; COVID-19 - immunology; COVID-19 - virology; Engineering and Technology; High-Throughput Nucleotide Sequencing - methods; High-throughput screening (Biochemical assaying); Humans; Immune response; Medicine and Health Sciences; Methods; Physiological aspects; Receptors, Antigen, B-Cell - genetics; Receptors, Antigen, B-Cell - immunology; Receptors, Antigen, T-Cell - genetics; Receptors, Antigen, T-Cell - immunology; Research and Analysis Methods; SARS-CoV-2 - genetics; SARS-CoV-2 - immunology; Single-Cell Analysis - methods; Software; T-Lymphocytes - immunology; Workflow; United States
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1012265

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets.