DeepNano: Deep Recurrent Neural Networks for Base Calling in MinION Nanopore Reads

Preprint of the paper is available at arXiv.org

DeepNano is an alternative basecaller for Oxford Nanopore MinION reads based on deep recurrent neural networks. Currently it works with SQK-MAP-006 and SQK-MAP-005 chemistry and as a postprocessor for Metrichor.

Here are our benchmarks, which compare mapping accuracy of reads produced by DeepNano and Metrichor from Oxford Nanopore. We trained on reads which align to half of the E. coli reference and tested on the other half of E. coli and on Klebsiela pneumoniae:

Ecoli
Metrichor
Ecoli
DeepNano
Klebsiella
Metrichor
Klebsiella
DeepNano
Template reads 71.3% 77.9% 68.1% 76.3%
Complement reads 71.4% 76.4% 69.5% 75.7%
2D reads 86.8% 88.5% 84.8% 86.7%

Download DeepNano at bitbucket repository

Datasets used for evaluation