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Nat Commun. 2018 Feb 8;9(1):561. doi: 10.1038/s41467-018-02832-w.

High-throughput immune repertoire analysis with IGoR.

Author information

1
Laboratoire de Physique Théorique, CNRS, Sorbonne Université and École Normale Supérieure (PSL), 24, Rue Lhomond, 75005, Paris, France.
2
Laboratoire de Physique Statistique, CNRS, Sorbonne Université, Université Paris-Diderot, and École normale supérieure (PSL), 24, Rue Lhomond, 75005, Paris, France. tmora@lps.ens.fr.
3
Laboratoire de Physique Théorique, CNRS, Sorbonne Université and École Normale Supérieure (PSL), 24, Rue Lhomond, 75005, Paris, France. awalczak@lpt.ens.fr.

Abstract

High-throughput immune repertoire sequencing is promising to lead to new statistical diagnostic tools for medicine and biology. Successful implementations of these methods require a correct characterization, analysis, and interpretation of these data sets. We present IGoR (Inference and Generation Of Repertoires)-a comprehensive tool that takes B or T cell receptor sequence reads and quantitatively characterizes the statistics of receptor generation from both cDNA and gDNA. It probabilistically annotates sequences and its modular structure can be used to investigate models of increasing biological complexity for different organisms. For B cells, IGoR returns the hypermutation statistics, which we use to reveal co-localization of hypermutations along the sequence. We demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization.

PMID:
29422654
PMCID:
PMC5805751
DOI:
10.1038/s41467-018-02832-w
[Indexed for MEDLINE]
Free PMC Article

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