HycDemux: a hybrid unsupervised approach for accurate barcoded sample demultiplexing in nanopore sequencing

Renmin Han, Junhai Qi, Yang Xue, Xiujuan Sun, Fa Zhang*, Xin Gao*, Guojun Li*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

DNA barcodes enable Oxford Nanopore sequencing to sequence multiple barcoded DNA samples on a single flow cell. DNA sequences with the same barcode need to be grouped together through demultiplexing. As the number of samples increases, accurate demultiplexing becomes difficult. We introduce HycDemux, which incorporates a GPU-parallelized hybrid clustering algorithm that uses nanopore signals and DNA sequences for accurate data clustering, alongside a voting-based module to finalize the demultiplexing results. Comprehensive experiments demonstrate that our approach outperforms unsupervised tools in short sequence fragment clustering and performs more robustly than current state-of-the-art demultiplexing tools for complex multi-sample sequencing data.

Original languageEnglish (US)
Article number222
JournalGenome biology
Volume24
Issue number1
DOIs
StatePublished - Dec 2023

Bibliographical note

Publisher Copyright:
© 2023, BioMed Central Ltd., part of Springer Nature.

Keywords

  • Clustering
  • Demultiplexing
  • Nanopore sequencing

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

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