Analyzing Antibody Repertoire Using Next-Generation Sequencing and Machine Learning.

Journal: Methods in molecular biology (Clifton, N.J.)
Published Date:

Abstract

Advances in high-throughput sequencing technologies have enabled comprehensive sequencing of the immune repertoire. Since repertoire analysis can help to explain the relationship between the immune system and diseases, several methods have been developed for repertoire analysis. Here, using simulated and real-world datasets, we describe how to use DeepRC, a method that applies cutting-edge machine learning techniques.

Authors

  • Shuto Hayashi
    Department of Preventive Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Shumpei Ishikawa
    Department of Preventive Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-0033, Japan. ishum-prm@m.u-tokyo.ac.jp.