Nature Communications (Jul 2021)

A deep learning model for predicting next-generation sequencing depth from DNA sequence

  • Jinny X. Zhang,
  • Boyan Yordanov,
  • Alexander Gaunt,
  • Michael X. Wang,
  • Peng Dai,
  • Yuan-Jyue Chen,
  • Kerou Zhang,
  • John Z. Fang,
  • Neil Dalchau,
  • Jiaming Li,
  • Andrew Phillips,
  • David Yu Zhang

DOI
https://doi.org/10.1038/s41467-021-24497-8
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 10

Abstract

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DNA probes used in next generation sequencing (NGS) have variable hybridisation kinetics, resulting in non-uniform coverage. Here, the authors develop a deep learning model to predict NGS depth using DNA probe sequences and apply to human and non-human sequencing panels.