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CAMISIM: simulating metagenomes and microbial communities.

Adrian Fritz1, Peter Hofmann1,2, Stephan Majda1,2

  • 1Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, 38124, Germany.

Microbiome
|February 10, 2019
PubMed
Summary

CAMISIM is a new software tool that simulates microbial communities and metagenome data. This tool generates benchmark datasets for evaluating analysis software performance and aids in understanding microbial community dynamics.

Keywords:
BenchmarkingCAMIGenome binningMetagenome assemblyMetagenomics softwareMicrobial communitySimulationTaxonomic binningTaxonomic profiling

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Computational Biology

Background:

  • Shotgun metagenome datasets exhibit high diversity due to biological variation, lab protocols, replicate numbers, and sequencing technologies.
  • Assessing metagenomic analysis software performance necessitates a diverse range of benchmark datasets.

Purpose of the Study:

  • To introduce CAMISIM, a microbial community and metagenome simulator.
  • To generate benchmark datasets with ground truth standards for evaluating metagenomic analysis tools.
  • To investigate the impact of various factors on metagenome assembler performance.

Main Methods:

  • CAMISIM models microbial abundance profiles, time series, and differential abundance studies.
  • It simulates second- and third-generation sequencing data from taxonomic profiles or de novo.
  • Gold standards are generated for sequence assembly, genome binning, and taxonomic profiling.

Main Results:

  • CAMISIM generated benchmark datasets for the first CAMI challenge.
  • Simulated gut microbiome datasets showed high functional congruence with real data.
  • The study investigated the effects of genome divergence, sequencing depth, and read errors on assemblers MEGAHIT and metaSPAdes.

Conclusions:

  • CAMISIM simulates diverse microbial communities and metagenome datasets with truth standards for method evaluation.
  • The software and all generated datasets are publicly available.
  • CAMISIM is a valuable resource for benchmarking and advancing metagenomic analysis.