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Sequencing of mRNA from Whole Blood using Nanopore Sequencing
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DeepSimulator: a deep simulator for Nanopore sequencing.

Yu Li1, Renmin Han1, Chongwei Bi2

  • 1Computational Bioscience Research Center (CBRC), Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, Thuwal, Saudi Arabia.

Bioinformatics (Oxford, England)
|April 17, 2018
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Summary
This summary is machine-generated.

DeepSimulator, a novel deep learning model, accurately mimics Oxford Nanopore sequencing's electrical signals and generates realistic sequencing reads. This tool aids in developing new bioinformatics tools for genome assembly and variant detection.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Oxford Nanopore sequencing generates vast amounts of data, necessitating advanced analytical tools.
  • Current Nanopore simulators lack the ability to accurately model the complex raw electrical signal generation process.
  • A versatile simulator is crucial for benchmarking new bioinformatics tools and complementing experimental data.

Purpose of the Study:

  • To develop a deep learning-based simulator, DeepSimulator, for mimicking the entire Oxford Nanopore sequencing pipeline.
  • To generate realistic raw electrical current signals and simulated sequencing reads.
  • To provide a tool that enhances the development of downstream bioinformatics applications.

Main Methods:

  • A context-dependent deep learning model is employed to simulate electrical current signals from reference genomes or contigs.
  • A base-calling procedure is integrated to generate simulated sequencing reads from the simulated signals.
  • The simulator allows users to adjust read accuracy from 83% to 97%.

Main Results:

  • DeepSimulator's context-dependent model generates signals more similar to experimental data than existing context-independent models.
  • Simulated reads generated with default parameters exhibit properties comparable to real Nanopore sequencing data.
  • Case studies demonstrate DeepSimulator's utility in advancing de novo assembly and low-coverage SNP detection.

Conclusions:

  • DeepSimulator offers a more natural and accurate simulation of the Nanopore sequencing process.
  • The tool effectively supports the development and benchmarking of bioinformatics tools.
  • DeepSimulator is freely available, promoting wider adoption and advancement in the field.