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Updated: May 21, 2026
08:43
Metagenomic Analysis of Silage
Published on: January 13, 2017
Computational methods for the analysis of tag sequences in metagenomics studies
Qin Chang1, Yihui Luan, Ting Chen
1School of Mathematics, Shandong University, Jinan, Shandong 250100, PR China.
Frontiers in Bioscience (Scholar Edition)
|June 2, 2012
Summary
This study reviews computational methods for analyzing metagenomic tag sequences. It addresses challenges in understanding microbial communities from large datasets generated by new sequencing technologies.
Area of Science:
- Microbiology
- Bioinformatics
- Environmental Science
Background:
- Metagenomics involves studying genetic material from uncultured environmental samples.
- Large-scale projects in human, marine, and soil science generate vast metagenomic data.
- Analyzing this data is challenging for understanding microbial communities and their interactions.
Purpose of the Study:
- To review computational methods for metagenomic data analysis.
- To address challenges in analyzing microbial assemblage and community comparison.
- To focus on methods for analyzing tag sequences in metagenomics.
Main Methods:
- Utilizes new sequencing technologies like Sanger, Illumina Solexa, and Roche 454.
- Focuses on the analysis of tag sequences, primarily 16S or 18S ribosomal RNA genes.
- Also considers whole metagenome shotgun sequencing approaches.
Main Results:
- Identifies and reviews various computational approaches for tag sequence analysis.
- Highlights the importance of efficient analysis for ecological and environmental studies.
- Provides an overview of current methodologies in metagenomic data interpretation.
Conclusions:
- Computational methods are crucial for interpreting large metagenomic datasets.
- Tag sequence analysis is a key approach for understanding microbial ecology.
- Efficient analysis enables deeper insights into microbial communities and their environments.
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