Pair consensus decoding improves accuracy of neural network basecallers for nanopore sequencing.

Journal: Genome biology
Published Date:

Abstract

We develop a general computational approach for improving the accuracy of basecalling with Oxford Nanopore's 1D and related sequencing protocols. Our software PoreOver ( https://github.com/jordisr/poreover ) finds the consensus of two neural networks by aligning their probability profiles, and is compatible with multiple nanopore basecallers. When applied to the recently-released Bonito basecaller, our method reduces the median sequencing error by more than half.

Authors

  • Jordi Silvestre-Ryan
    Department of Bioengineering, University of California, Berkeley, 94720, USA. jordisr@berkeley.edu.
  • Ian Holmes
    Department of Bioengineering, University of California, Berkeley, 94720, USA. ihh@berkeley.edu.