Published April 7, 2023 | Version 1.0.0
Dataset Open

Fibertools: fast and accurate m6A calling using single-molecule long-read sequencing (ML data)

Authors/Creators

  • 1. Department of Genome Sciences, University of Washington, Seattle, WA, USA
  • 2. Division of Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA
  • 3. Department of Statistics, University of Washington, Seattle, WA, USA
  • 4. Department of Medical Chemistry, University of Washington, Seattle, WA, USA
  • 5. Department of Genome Sciences, University of Washington, Seattle, WA, USA; Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA

Description

Fibertools is a convolutional neural network that permits the fast and accurate identification of endogenous and exogenous N6-methyladenine (m6A)-marked bases using single-molecule long-read sequencing. This dataset (ML data) provides training and validation data for training fibertools supervised and semi-supervised CNN models for three long-read chemistries.

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