ArticleGenome research2024
Simulation of nanopore sequencing signal data with tunable parameters.
Article in Genome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Review
- NanoSimFormer: an end-to-end transformer-based nanopore signal simulator with basecaller guidance.Bioinformatics (Oxford, England) · 2026Article
- Nanopore direct RNA sequencing and the epitranscriptome: Advances in mapping native RNA landscapes.iMeta · 2026Review
- Direct high-throughput deconvolution of non-canonical bases via nanopore sequencing and bootstrapped learning.Nature communications · 2025Article
- A new compression strategy to reduce the size of nanopore sequencing data.Genome research · 2025Article
- De novo non-canonical nanopore basecalling enables private communication using heavily-modified DNA data at single-molecule level.Nature communications · 2025Article
- End-to-end simulation of nanopore sequencing signals with feed-forward transformers.Bioinformatics (Oxford, England) · 2024Article
- TDFPS-Designer: an efficient toolkit for barcode design and selection in nanopore sequencing.Genome biology · 2024Article
- A telomere-to-telomere Eucalyptus regnans genome: unveiling haplotype variance in structure and genes within one of the world's tallest trees.BMC genomics · 2024Article
- Interactive visualization of nanopore sequencing signal data with Squigualiser.Bioinformatics (Oxford, England) · 2024Article
- Sigmoni: classification of nanopore signal with a compressed pangenome index.Bioinformatics (Oxford, England) · 2024Article
- Icarust, a real-time simulator for Oxford Nanopore adaptive sampling.Bioinformatics (Oxford, England) · 2024Article
- Streamlining remote nanopore data access with slow5curl.GigaScience · 2024Article
- Efficient end-to-end long-read sequence mapping using minimap2-fpga integrated with hardware accelerated chaining.Scientific reports · 2023Article
- Sigmoni: classification of nanopore signal with a compressed pangenome index.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In silico simulation of high-throughput sequencing data is a technique used widely in the genomics field. However, there is currently a lack of effective tools for creating simulated data from nanopore sequencing devices, which measure DNA or RNA molecules in the form of time-series current signal data. Here, we introduce Squigulator, a fast and simple tool for simulation of realistic nanopore signal data. Squigulator takes a reference genome, a transcriptome, or read sequences, and generates corresponding raw nanopore signal data. This is compatible with basecalling software from Oxford Nanopore Technologies (ONT) and other third-party tools, thereby providing a useful substrate for development, testing, debugging, validation, and optimization at every stage of a nanopore analysis workflow. The user may generate data with preset parameters emulating specific ONT protocols or noise-free "ideal" data, or they may deterministically modify a range of experimental variables and/or noise parameters to shape the data to their needs. We present a brief example of Squigulator's use, creating simulated data to model the degree to which different parameters impact the accuracy of ONT basecalling and downstream variant detection. This analysis reveals new insights into the nature of ONT data and basecalling algorithms. We provide Squigulator as an open-source tool for the nanopore community.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.