Determining optical mapping errors by simulations
Status PubMed-not-MEDLINE Jazyk angličtina Země Anglie, Velká Británie Médium print
Typ dokumentu časopisecké články
Grantová podpora
SGS project
SP2021/94
VSB-Technical University of Ostrava
NU20-06-00269
Ministry of Health
Grant-CZ-102
Celgene Research
PubMed
33983386
DOI
10.1093/bioinformatics/btab259
PII: 6275255
Knihovny.cz E-zdroje
- Publikační typ
- časopisecké články MeSH
MOTIVATION: Optical mapping is a complementary technology to traditional DNA sequencing technologies, such as next-generation sequencing (NGS). It provides genome-wide, high-resolution restriction maps from single, stained molecules of DNA. It can be used to detect large and small structural variants, copy number variations and complex rearrangements. Optical mapping is affected by different kinds of errors in comparison with traditional DNA sequencing technologies. It is important to understand the source of these errors and how they affect the obtained data. This article proposes a novel approach to modeling errors in the data obtained from the Bionano Genomics Inc. Saphyr system with Direct Label and Stain (DLS) chemistry. Some studies have already addressed this issue for older instruments with nicking enzymes, but we are unaware of a study that addresses this new system. RESULTS: The main result is a framework for studying errors in the data obtained from the Saphyr instrument with DLS chemistry. The framework's main component is a simulation that computes how major sources of errors for this instrument (a false site, a missing site and resolution errors) affect the distribution of fragment lengths in optical maps. The simulation is parametrized by variables describing these errors and we are using a differential evolution algorithm to evaluate parameters that best fit the data from the instrument. Results of the experiments manifest that this approach can be used to study errors in the optical mapping data analysis. AVAILABILITY AND IMPLEMENTATION: Source codes supporting the presented results are available at: https://github.com/mvasinek/olgen-om-error-prediction. The data underlying this article are available on the Bionano Genomics Inc. website, at: https://bionanogenomics.com/library/datasets/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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