Strainer: Software for analysis of population variation in community genomic datasets

Eppley John M., Tyson Gene W., Getz Wayne M. and Banfield Jillian F. (2007) Strainer: Software for analysis of population variation in community genomic datasets. BMC Bioinformatics, 8 398: 1-11. doi:10.1186/1471-2105-8-398

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Author Eppley John M.
Tyson Gene W.
Getz Wayne M.
Banfield Jillian F.
Title Strainer: Software for analysis of population variation in community genomic datasets
Journal name BMC Bioinformatics   Check publisher's open access policy
ISSN 1471-2105
Publication date 2007-10-17
Year available 2007
Sub-type Article (original research)
DOI 10.1186/1471-2105-8-398
Open Access Status DOI
Volume 8
Issue 398
Start page 1
End page 11
Total pages 11
Place of publication London, U.K.
Publisher BioMed Central
Language eng
Subject 03 Chemical Sciences
0304 Medicinal and Biomolecular Chemistry
0601 Biochemistry and Cell Biology
1099 Other Technology
Abstract Background: Metagenomic analyses of microbial communities that are comprehensive enough to provide multiple samples of most loci in the genomes of the dominant organism types will also reveal patterns of genetic variation within natural populations. New bio-informatic tools will enable visualization and comprehensive analysis of this sequence variation and inference of recent evolutionary and ecological processes. Results: We have developed a software package for analysis and visualization of genetic variation in populations and reconstruction of strain variants from otherwise co-assembled sequences. Sequencing reads can be clustered by matching patterns of single nucleotide polymorphisms to generate predicted gene and protein variant sequences, identify conserved intergenic regulatory sequences, and determine the quantity and distribution of recombination events. Conclusion: The Strainer software, a first generation metagenomic bioinformatics tool, facilitates comprehension and analysis of heterogeneity intrinsic in natural communities. The program reveals the degree of clustering among closely related sequence variants and provides a rapid means to generate gene and protein sequences for functional, ecological, and evolutionary analyses.
Keyword Software
Bioinformatic tools
Metagenomic analyses
Q-Index Code C1
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
School of Chemistry and Molecular Biosciences
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Citation counts: TR Web of Science Citation Count  Cited 22 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 25 times in Scopus Article | Citations
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Created: Tue, 22 Dec 2009, 21:11:10 EST by Macushla Boyle on behalf of Faculty of Science