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

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.

Results

The method is evaluated on acquired images of human DNA molecules stretched in nano-channels. The accuracy of the method is benchmarked against state-of-the-art commercial software Bionano Solve. The results show a significant advantage in alignment success rate for molecules

SUBMITTER: Nogin Y 

PROVIDER: S-EPMC10049785 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature