High-throughput immune repertoire analysis with IGoR

Quentin Marcou, Thierry Mora () and Aleksandra M. Walczak ()
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Quentin Marcou: Sorbonne Université and École Normale Supérieure (PSL)
Thierry Mora: Sorbonne Université, Université Paris-Diderot, and École normale supérieure (PSL)
Aleksandra M. Walczak: Sorbonne Université and École Normale Supérieure (PSL)

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: 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.

Date: 2018
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DOI: 10.1038/s41467-018-02832-w

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