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

Abstract We develop a general computational approach for improving the accuracy of basecalling with Oxford Nanopore’s 1D2 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.