DeepOM: single-molecule optical genome mapping via deep learning.

Journal: Bioinformatics (Oxford, England)
PMID: 36929928

Abstract

MOTIVATION: Efficient tapping into genomic information from a single microscopic image of an intact DNA molecule is an outstanding challenge and its solution will open new frontiers in molecular diagnostics. Here, a new computational method for optical genome mapping utilizing deep learning is presented, termed DeepOM. Utilization of a convolutional neural network, trained on simulated images of labeled DNA molecules, improves the success rate in the alignment of DNA images to genomic references.

Authors

  • Yevgeni Nogin
    Russel Berrie Nanotechnology Institute, Technion, Haifa 320003, Israel.
  • Tahir Detinis Zur
    Raymond and Beverly Sackler Faculty of Exact Sciences, Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv 6997801, Israel.
  • Sapir Margalit
    Raymond and Beverly Sackler Faculty of Exact Sciences, Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv 6997801, Israel.
  • Ilana Barzilai
    Department of Biomedical Engineering, Technion, Haifa 320003, Israel.
  • Onit Alalouf
    Department of Biomedical Engineering, Lorry I. Lokey Center for Life Sciences and Engineering, Technion, Haifa, Israel.
  • Yuval Ebenstein
    Raymond and Beverly Sackler Faculty of Exact Sciences, Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv 6997801, Israel.
  • Yoav Shechtman
    Department of Biomedical Engineering; Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering. Electronic address: yoavsh@bm.technion.ac.il.

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