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CuReSim-LoRM: A Tool to Simulate Metabarcoding Long Reads.

Yasmina Mesloub1, Delphine Beury1, Félix Vandermeeren1

  • 1Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, US 41-UAR 2014-PLBS, F-59000 Lille, France.

International Journal of Molecular Sciences
|September 28, 2023
PubMed
Summary

A new tool, CuReSim-LoRM, simulates long reads for microbial DNA metabarcoding, mimicking error rates and length distributions. This helps benchmark analysis pipelines and improve microbial community studies.

Keywords:
benchmarklong readsmetabarcodingread simulation

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Area of Science:

  • Microbial Ecology
  • Bioinformatics
  • Genomics

Background:

  • Metabarcoding DNA sequencing advances microbial community analysis.
  • Third-generation sequencing offers long reads for higher taxonomic resolution.
  • Oxford Nanopore Technologies (ONT) long reads have high error rates, introducing analytical biases.

Purpose of the Study:

  • To develop a tool for simulating long metabarcoding reads.
  • To mimic real-world error rates and length distributions for benchmarking.
  • To address the lack of specific simulators for long-read metabarcoding data.

Main Methods:

  • Introduction of CuReSim-LoRM, a customized read simulator for long metabarcoding reads.
  • Generation of simulated reads with controllable error rates and length distributions.
  • Validation of simulator's ability to mimic real ONT sequencing data.

Main Results:

  • CuReSim-LoRM successfully generates long reads for metabarcoding.
  • The simulator effectively mimics varying error rates and length distributions.
  • Simulated data closely resembles real sequencing data, enabling robust benchmarking.

Conclusions:

  • CuReSim-LoRM provides a valuable resource for benchmarking metabarcoding analysis pipelines.
  • Accurate simulation of long reads is crucial for understanding and mitigating biases.
  • The tool facilitates more reliable interpretation of microbial community structures from long-read sequencing data.