Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning
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Summary
This work reports the first deep learning model, named Chiron, that can directly translate the raw signal to DNA sequence without the error-prone segmentation step, and shows that this model provides state-of-the-art basecalling accuracy when trained with only a small set of 4000 reads.
- Type
- preprint
- Published
- 2017-08-23
- Cited by
- 159
- References
- 40
- Access
- Open access
- OpenAlex
- https://openalex.org/W2749642998
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:4810901
Keywords
Nanopore sequencing, Nanopore, Sequence (biology), Graphics, Computer science
References
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- Bidirectional recurrent neural networks
- Learning to Forget: Continual Prediction with LSTM
- Single-nucleotide discrimination in immobilized DNA oligonucleotides with a biological nanopore
- Streaming algorithms for identification of pathogens and antibiotic resistance potential from real-time MinIONTM sequencing
- Realtime analysis and visualization of MinION sequencing data with npReader
- Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin
- Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences
- Deep Residual Learning for Image Recognition
- Real-time, portable genome sequencing for Ebola surveillance
- DeepNano: Deep recurrent neural networks for base calling in MinION nanopore reads
- Fast and sensitive mapping of nanopore sequencing reads with GraphMap
Cited by
- The long reads ahead: de novo genome assembly using the MinION
- DeepSimulator: a deep simulator for Nanopore sequencing
- Nanopore sequencing technology and tools for genome assembly: computational analysis of the current state, bottlenecks and future directions
- Piercing the dark matter: bioinformatics of long-range sequencing and mapping
- Deep learning of genomic variation and regulatory network data.
- Deepbinner: Demultiplexing barcoded Oxford Nanopore reads with deep convolutional neural networks
- From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy
- Nanopore sequence-based genome assembly of the basmati rice
- Resolving the complex Bordetella pertussis genome using barcoded nanopore sequencing
- MinION rapid sequencing: Review of potential applications in neurosurgery
- Mapping DNA replication with nanopore sequencing
- Applying Multiple Knowledge to Sussex-Huawei Locomotion Challenge
- BRAWL: A Spintronics-Based Portable Basecalling-in-Memory Architecture for Nanopore Genome Sequencing
- A primer on deep learning in genomics
- WaveNano: a signal-level nanopore base-caller via simultaneous prediction of nucleotide labels and move labels through bi-directional WaveNets
- Performance of neural network basecalling tools for Oxford Nanopore sequencing
- Deep learning in bioinformatics: introduction, application, and perspective in big data era
- Increasing the accuracy of nanopore DNA sequencing using a time-varying cross membrane voltage
- Nanopore sequencing: Review of potential applications in functional genomics
- Learning shapelets for improving the single-molecule nanopore sensing.
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