Simulation of nanopore sequencing signal data with tunable parameters

Area of Science:

• Genomics
• Bioinformatics

Background:

• In silico simulation is crucial for high-throughput sequencing data analysis.
• Existing tools lack effective simulation capabilities for nanopore sequencing, which generates time-series current signal data.

Purpose of the Study:

• To introduce Squigulator, a novel tool for simulating realistic nanopore signal data.
• To provide a versatile platform for developing, testing, and optimizing nanopore sequencing analysis pipelines.

Main Methods:

• Squigulator simulates raw nanopore signal data from reference genomes, transcriptomes, or read sequences.
• The tool supports preset parameters for specific Oxford Nanopore Technologies (ONT) protocols or noise-free data.
• Users can modify experimental and noise parameters for customized data generation.

Main Results:

• Simulated data is compatible with ONT basecalling software and third-party tools.
• Squigulator facilitates the modeling of parameter impacts on basecalling accuracy and variant detection.
• Analysis using simulated data provides new insights into ONT data characteristics and basecalling algorithms.

Conclusions:

• Squigulator is a fast, simple, and open-source tool for the nanopore community.
• It enhances the development and validation stages of nanopore data analysis workflows.
• The tool aids in understanding factors influencing nanopore sequencing data quality and analysis outcomes.