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Nanopore Basecalling from a Perspective of Instance Segmentation by Zhang, Yao-zhong; Akdemir, Arda; Tremmel, Georg; Imoto, Seiya; Miyano, Satoru; Shibuya, Tetsuo; Yamaguchi, Rui is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Nanopore Basecalling from a Perspective of Instance Segmentation about?

## Background Nanopore sequencing is a rapidly developing third-generation sequencing technology, which can generate long nucleotide reads of molecules within a portable device in real-time. Through detecting the change of ion currency signals during a DNA/RNA fragment’s pass through a nanopore, genotypes are determined. Currently, the accuracy of nanopore basecalling has a higher error rate than the basecalling of short-read sequencing. Through utilizing deep neural networks, the-state-of-the art nanopore basecallers achieve basecalling accuracy in a range from 85% to 95%. ## Result In this work, we proposed a novel basecalling approach from a perspective of instance segmentation. Different from previous approaches of doing typical sequence labeling, we formulated the basecalling problem as a multi-label segmentation task. Meanwhile, we proposed a refined U-net model which we call UR-net that can model sequential dependencies for a one-dimensional segmentation task. The experiment results show that the proposed basecaller URnano achieves competitive results on the in-species data, compared to the recently proposed CTC-featured basecallers. ## Conclusion Our results show that formu

Who reads Nanopore Basecalling from a Perspective of Instance Segmentation?

Author

Zhang, Yao-zhong; Akdemir, Arda; Tremmel, Georg; Imoto, Seiya; Miyano, Satoru; Shibuya, Tetsuo; Yamaguchi, Rui

Publisher

BioMed Central; Springer (Biomed Central Ltd.); [London]: BioMed Central, [2000]-; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc. (ISSN 1471-2105)

Published

2020

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)