Design of optimal labeling patterns for optical genome mapping via information theory

Abstract Motivation Optical genome mapping (OGM) is a technique that extracts partial genomic information from optically imaged and linearized DNA fragments containing fluorescently labeled short sequence patterns. This can be used for various analyses applications, such as the detection of structural variations copy-number variations, epigenomic profiling, microbial species identification. Currently, choice patterns based on available bio-chemical methods, not necessarily optimized application. Results In this work, we develop model OGM theory, which enables design optimal labeling specific applications target organism genomes. We validated through experimental human simulations bacterial DNA. Our predicts up to 10-fold improved accuracy by patterns, may guide future development methods significantly improve its yield profiling cultivation-free pathogen identification in clinical samples. Availability implementation https://github.com/yevgenin/PatternCode