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Sci Rep. 2016 Apr 22;6:23901. doi: 10.1038/srep23901.

Clonify: unseeded antibody lineage assignment from next-generation sequencing data.

Briney B1,2,3, Le K1,2,3, Zhu J1,2,3, Burton DR1,2,3,4.

Author information

1
Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, CA 92037, USA.
2
International AIDS Vaccine Initiative Neutralizing Antibody Center, The Scripps Research Institute, La Jolla, CA 92037, USA.
3
Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery, The Scripps Research Institute, La Jolla, CA 92037, USA.
4
Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard University, Boston, MA 02142, USA.

Abstract

Defining the dynamics and maturation processes of antibody clonal lineages is crucial to understanding the humoral response to infection and immunization. Although individual antibody lineages have been previously analyzed in isolation, these studies provide only a narrow view of the total antibody response. Comprehensive study of antibody lineages has been limited by the lack of an accurate clonal lineage assignment algorithm capable of operating on next-generation sequencing datasets. To address this shortcoming, we developed Clonify, which is able to perform unseeded lineage assignment on very large sets of antibody sequences. Application of Clonify to IgG+ memory repertoires from healthy individuals revealed a surprising lack of influence of large extended lineages on the overall repertoire composition, indicating that this composition is driven less by the order and frequency of pathogen encounters than previously thought. Clonify is freely available at www.github.com/briney/clonify-python.

PMID:
27102563
PMCID:
PMC4840318
DOI:
10.1038/srep23901
[Indexed for MEDLINE]
Free PMC Article

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