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DIAMOND +  MEGAN Microbiome Analysis.

Anupam Gautam1,2, Wenhuan Zeng1, Daniel H Huson3

  • 1Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.

Methods in Molecular Biology (Clifton, N.J.)
|May 31, 2023
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Summary
This summary is machine-generated.

This study demonstrates the DIAMOND+MEGAN pipeline for analyzing microbiome data. It efficiently determines taxonomic and functional composition from short and long-read sequencing, aiding comparative metagenomics research.

Keywords:
Functional binningMetagenomicsSequence alignmentSoftwareTaxonomic binning

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Metagenomics analyzes microbial communities using DNA sequencing.
  • Key tasks include identifying taxonomic and functional composition and correlating it with external factors.
  • Current approaches often involve aligning sequences to reference databases for classification.

Purpose of the Study:

  • To illustrate the application of the DIAMOND+MEGAN pipeline for metagenomic analysis.
  • To demonstrate how to determine taxonomic and functional composition of microbiomes.
  • To showcase the comparison of microbial communities using sequencing data.

Main Methods:

  • Utilizing the DIAMOND aligner for sequence similarity searches against protein databases (e.g., NCBI-nr).
  • Employing the MEGAN tool for taxonomic and functional binning based on sequence alignments.
  • Applying the pipeline to both short-read and long-read sequencing datasets.

Main Results:

  • Successful taxonomic and functional profiling of microbial communities from diverse datasets.
  • Demonstration of interactive analysis and comparison of metagenomic data.
  • Validation of the DIAMOND+MEGAN pipeline's effectiveness on different sequencing technologies.

Conclusions:

  • The DIAMOND+MEGAN pipeline provides an effective method for comprehensive metagenomic analysis.
  • This approach facilitates the understanding of microbiome composition and function.
  • The pipeline is applicable to various sequencing data types, supporting comparative microbiome studies.