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bioRxiv · 10.1101/2024.01.18.576147

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

Gabernet, G.·Marquez, S.·Bjornson, R.·Peltzer, A.·Meng, H.·Aron, E.·Lee, N. Y.·Jensen, C.·Ladd, D.·Hanssen, F.·Heumos, S.·nf-core community,·Yaari, G.·Kowarik, M. C.·Nahnsen, S.·Kleinstein, S. H.
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Abstract

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. Availability and implementationnf-core/airrflow is available free of charge, under the MIT license on GitHub (https://github.com/nf-core/airrflow). Detailed documentation and example results are available on the nf-core website at (https://nf-co.re/airrflow). Visual abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/576147v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@e39504org.highwire.dtl.DTLVardef@14c52aforg.highwire.dtl.DTLVardef@1c87664org.highwire.dtl.DTLVardef@1d4d78b_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Gabernet, G., Marquez, S., Bjornson, R., Peltzer, A., Meng, H., Aron, E., Lee, N. Y., Jensen, C., Ladd, D., Hanssen, F., Heumos, S., nf-core community,, Yaari, G., Kowarik, M. C., Nahnsen, S., Kleinstein, S. H.. 2024-01-20. nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework. https://doi.org/10.1101/2024.01.18.576147

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