Nanopore Base Calling on the Edge
November 09, 2020 ยท Entered Twilight ยท ๐ Bioinform.
"Last commit was 5.0 years ago (โฅ5 year threshold)"
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Repo contents: .gitignore, README.md, backend.py, basecall.py, networks, requirements.txt
Authors
Peter Pereลกรญni, Vladimรญr Boลพa, Broลa Brejovรก, Tomรกลก Vinaล
arXiv ID
2011.04312
Category
cs.LG: Machine Learning
Cross-listed
q-bio.GN
Citations
49
Venue
Bioinform.
Repository
https://github.com/fmfi-compbio/coral-basecaller
โญ 12
Last Checked
4 months ago
Abstract
We developed a new base caller DeepNano-coral for nanopore sequencing, which is optimized to run on the Coral Edge Tensor Processing Unit, a small USB-attached hardware accelerator. To achieve this goal, we have designed new versions of two key components used in convolutional neural networks for speech recognition and base calling. In our components, we propose a new way of factorization of a full convolution into smaller operations, which decreases memory access operations, memory access being a bottleneck on this device. DeepNano-coral achieves real-time base calling during sequencing with the accuracy slightly better than the fast mode of the Guppy base caller and is extremely energy efficient, using only 10W of power. Availability: https://github.com/fmfi-compbio/coral-basecaller
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