ArticleBioinformatics (Oxford, England)2018
Modelling BioNano optical data and simulation study of genome map assembly.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review: Long-Read Sequencing in Algal Studies.International journal of molecular sciences · 2026Pooled it
- Electronic Mapping of a Bacterial Genome with Dual Solid-State Nanopores and Active Single-Molecule Control.ACS nano · 2022Article
- Robust Benchmark Structural Variant Calls of An Asian Using State-of-the-art Long-read Sequencing Technologies.Genomics, proteomics & bioinformatics · 2022Article
- Filling gaps of genome scaffolds via probabilistic searching optical maps against assembly graph.BMC bioinformatics · 2021Article
- Fast and efficient Rmap assembly using the Bi-labelled de Bruijn graph.Algorithms for molecular biology : AMB · 2021Article
- FaNDOM: Fast nested distance-based seeding of optical maps.Patterns (New York, N.Y.) · 2021Article
- Structural variant detection in cancer genomes: computational challenges and perspectives for precision oncology.NPJ precision oncology · 2021Review
- On the application, reporting, and sharing of in silico simulations for genetic studies.Genetic epidemiology · 2021Review
- Signal-based optical map alignment.PloS one · 2021Article
- Twelve quick steps for genome assembly and annotation in the classroom.PLoS computational biology · 2020Article
- AmpliconReconstructor integrates NGS and optical mapping to resolve the complex structures of focal amplifications.Nature communications · 2020Article
- Advances in optical mapping for genomic research.Computational and structural biotechnology journal · 2020Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: The launch of the BioNano next-generation mapping system has greatly enhanced the performance of physical map construction, thus rapidly expanding the application of optical mapping in genome research. Data biases have profound implications for downstream applications. However, very little is known about the properties and biases of BioNano data, and the very factors that contribute to whole-genome optical map assembly. Results: We generated BioNano molecule data from eight organisms with diverse base compositions. We first characterized the properties/biases of BioNano molecule data, i.e. molecule length distribution, false labelling signal, variation of optical resolution and coverage distribution bias, and their inducing factors such as chimeric molecules, fragile sites and DNA molecule stretching. Second, we developed the BioNano Molecule SIMulator (BMSIM), a novel computer simulation program for optical data. BMSIM, is of great use for future genome mapping projects. Third, we evaluated the experimental variables that impact whole-genome optical map assembly. Specifically, the effects of coverage depth, molecule length, false-positive and false-negative labelling signals, chimeric molecules and nicking enzyme and nick site density were investigated. Our simulation study provides the empirical findings on how to control experimental variables and gauge analytical parameters to maximize benefit and minimize cost on whole-genome optical map assembly. Availability and implementation: BMSIM is freely available on: https://github.com/pingchen09990102/BMSIM. Supplementary information: Supplementary data are available at Bioinformatics online.
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