  The Oxford Nanopore Technologies's MinION is the first portable DNA
sequencing device. It is capable of producing long reads, over 100 kBp were
reported. However, it has significantly higher error rate than other methods.
In this study, we present MinCall, an end2end basecaller model for the MinION.
The model is based on deep learning and uses convolutional neural networks
(CNN) in its implementation. For extra performance, it uses cutting edge deep
learning techniques and architectures, batch normalization and Connectionist
Temporal Classification (CTC) loss. The best performing deep learning model
achieves 91.4% median match rate on E. Coli dataset using R9 pore chemistry and
1D reads.
