Reconstructing antibody repertoires from error-prone immunosequencing reads

Alexander Shlemov, Sergey Bankevich, Andrey Bzikadze, Maria A. Turchaninova, Yana Safonova, Pavel A. Pevzner

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Transforming error-prone immunosequencing datasets into Ab repertoires is a fundamental problem in immunogenomics, and a prerequisite for studies of immune responses. Although various repertoire reconstruction algorithms were released in the last 3 y, it remains unclear how to benchmark them and how to assess the accuracy of the reconstructed repertoires. We describe an accurate IgReC algorithm for constructing Ab repertoires from high-throughput immunosequencing datasets and a new framework for assessing the quality of reconstructed repertoires. Surprisingly, Ab repertoires constructed by IgReC from barcoded immunosequencing datasets in the blind mode (without using information about unique molecular identifiers) improved upon the repertoires constructed by the state-of-the-art tools that use barcoding. This finding suggests that IgReC may alleviate the need to generate repertoires using the barcoding technology (the workhorse of current immunogenomics efforts) because our computational approach to error correction of immunosequencing data is nearly as powerful as the experimental approach based on barcoding.

Original languageEnglish (US)
Pages (from-to)3369-3380
Number of pages12
JournalJournal of Immunology
Volume199
Issue number9
DOIs
StatePublished - Nov 1 2017

All Science Journal Classification (ASJC) codes

  • Immunology and Allergy
  • Immunology

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