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Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data

View ORCID ProfileNima Nouri, View ORCID ProfileSteven H. Kleinstein
doi: https://doi.org/10.1101/788620
Nima Nouri
1Department of Pathology, Yale School of Medicine, New Haven, CT 06511, USA
2Center for Medical Informatics, Yale School of Medicine, New Haven, CT 06511, USA
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Steven H. Kleinstein
1Department of Pathology, Yale School of Medicine, New Haven, CT 06511, USA
2Center for Medical Informatics, Yale School of Medicine, New Haven, CT 06511, USA
3Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
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Abstract

Motivation Adaptive immune receptor repertoire sequencing (AIRR-Seq) offers the possibility of identifying and tracking B cell clonal expansions during adaptive immune responses. Members of a B cell clone are descended from a common ancestor and share the same initial V(D)J rearrangement, but their B cell receptore (BCR) sequence may differ due to the accumulation of somatic hypermutations (SHMs). Clonal relationships are learned from AIRR-seq data by analyzing the BCR sequence, with the most common methods focused on the highly diverse junction region. However, clonally related cells often share SHMs which have been accumulated during affinity maturation. Here, we investigate whether shared SHMs in the V and J segments of the BCR can be leveraged along with the junction sequence to improve the ability to identify clonally related sequences. We develop independent distance functions that capture junction similarity and shared mutations, and combine these in a spectral clustering framework to infer the BCR clonal relationships. Using both simulated and experimental data, we show that this model improves both the sensitivity and specificity for identifying B cell clones.

Availability Source code for this method is freely available in the SCOPer (Spectral Clustering for clOne Partitioning) R package (version 0.2 or later) in the Immcantation framework: www.immcantation.org under the CC BY-SA 4.0 license.

Contact steven.kleinstein{at}yale.edu

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted November 19, 2019.
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Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data
Nima Nouri, Steven H. Kleinstein
bioRxiv 788620; doi: https://doi.org/10.1101/788620
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Somatic hypermutation analysis for improved identification of B cell clonal families from next-generation sequencing data
Nima Nouri, Steven H. Kleinstein
bioRxiv 788620; doi: https://doi.org/10.1101/788620

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