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Related Experiment Video

Updated: Nov 5, 2025

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

Determining optical mapping errors by simulations.

Michal Vašinek¹, Marek Běhálek¹, Petr Gajdoš¹

¹Department of Computer Science, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava 708 00, Czech Republic.

Bioinformatics (Oxford, England)

|May 13, 2021

Summary

This study presents a new computational framework to model errors in optical mapping data from the Bionano Saphyr system. The approach uses simulation to understand how false sites, missing sites, and resolution errors impact fragment lengths, improving data analysis.

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Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT

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Published on: August 4, 2018

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Optical mapping complements DNA sequencing (e.g., next-generation sequencing) by creating high-resolution restriction maps from single DNA molecules.
It detects structural variants, copy number variations, and complex rearrangements, but is susceptible to unique error types compared to sequencing.
Understanding optical mapping error sources is crucial for accurate data interpretation, especially with newer technologies like Bionano's Direct Label and Stain (DLS) chemistry.

Purpose of the Study:

To develop and present a novel computational framework for modeling errors specific to the Bionano Genomics Saphyr system using Direct Label and Stain (DLS) chemistry.
To simulate the impact of major error sources (false sites, missing sites, resolution errors) on optical map fragment length distributions.
To provide a method for parameterizing and evaluating these error models against real-world instrument data.

Main Methods:

Developed a simulation-based framework to model optical mapping errors.
Incorporated key error types: false positive sites, false negative sites, and resolution errors.
Utilized a differential evolution algorithm to fit simulation parameters to experimental data.

Main Results:

The proposed framework successfully models the impact of various error sources on fragment length distributions in optical mapping data.
The simulation approach, parameterized by error variables, effectively fits data from the Saphyr instrument.
Demonstrated the utility of the framework for analyzing and understanding errors in optical mapping data.

Conclusions:

The developed framework provides a robust method for studying and quantifying errors in Bionano Saphyr DLS optical mapping data.
This approach enhances the reliability and accuracy of structural variant detection and other analyses using optical mapping.
The study addresses a gap in understanding errors for newer optical mapping chemistries and instruments.