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Related Experiment Video

Updated: May 15, 2026

Metagenomic Analysis of Silage
08:43

Metagenomic Analysis of Silage

Published on: January 13, 2017

Comparison of metagenomic samples using sequence signatures.

Bai Jiang1, Kai Song, Jie Ren

  • 1MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST / Department of Automation, Tsinghua University, Beijing 100084, China.

BMC Genomics
|December 28, 2012
PubMed
Summary

Sequence signatures effectively compare metagenomic samples from next-generation sequencing (NGS) data without needing reference databases. The d2S dissimilarity measure shows superior performance in revealing microbial community relationships and environmental factors.

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Last Updated: May 15, 2026

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Area of Science:

  • Genomics
  • Bioinformatics
  • Microbial Ecology

Background:

  • Sequence signatures (k-mer frequencies) are used for genomic comparisons and regulatory sequence analysis.
  • Next-generation sequencing (NGS) generates vast metagenomic data, posing assembly and analysis challenges.
  • Sequence-signature methods offer a database-independent approach for metagenomic analysis.

Purpose of the Study:

  • To evaluate sequence-signature-based dissimilarity measures for comparing metagenomic samples.
  • To identify the most effective measure for analyzing NGS metagenomic data.
  • To uncover environmental factors influencing microbial community composition.

Main Methods:

  • Compared various dissimilarity measures including d2, d2*, d2S, Hao, relative nucleotide frequencies, and lp measures.
  • Utilized extensive simulations and three real NGS metagenomic datasets (mammalian fecal, marine, human fecal).
  • Assessed performance based on clustering and recovery of environmental gradients.

Main Results:

  • The d2S dissimilarity measure demonstrated superior performance in clustering metagenomic samples.
  • d2S effectively recovered environmental gradients influencing microbial communities.
  • Identified associations between mammalian gut microbial signatures, diet, and physiology.
  • Revealed relationships between marine microbial signatures, location, and temperature.

Conclusions:

  • Sequence signatures can reveal relationships among metagenomic samples from NGS reads without database alignment.
  • The d2S dissimilarity measure is a robust and recommended choice for metagenomic comparisons.
  • Tuple size choice is influenced by sequencing depth but generally robust.