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Functional analysis of metagenomes and metatranscriptomes using SEED and KEGG.

Mitra S, Rupek P, Richter DC, Urich T, Gilbert JA, Meyer F, Wilke A, Huson DH - BMC Bioinformatics (2011)

Bottom Line: We have compared our results with the MG-RAST service for different datasets.The MEGAN program now allows the interactive analysis and comparison of the taxonomical and functional content of multiple datasets.As a stand-alone tool, MEGAN provides an alternative to web portals for scientists that have concerns about uploading their unpublished data to a website.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Bioinformatics ZBIT, Tübingen University, Sand 14, 72076 Tübingen, Germany. mitra@informatik.uni-tuebingen.de.

ABSTRACT

Background: Metagenomics is the study of microbial organisms using sequencing applied directly to environmental samples. Technological advances in next-generation sequencing methods are fueling a rapid increase in the number and scope of metagenome projects. While metagenomics provides information on the gene content, metatranscriptomics aims at understanding gene expression patterns in microbial communities. The initial computational analysis of a metagenome or metatranscriptome addresses three questions: (1) Who is out there? (2) What are they doing? and (3) How do different datasets compare? There is a need for new computational tools to answer these questions. In 2007, the program MEGAN (MEtaGenome ANalyzer) was released, as a standalone interactive tool for analyzing the taxonomic content of a single metagenome dataset. The program has subsequently been extended to support comparative analyses of multiple datasets.

Results: The focus of this paper is to report on new features of MEGAN that allow the functional analysis of multiple metagenomes (and metatranscriptomes) based on the SEED hierarchy and KEGG pathways. We have compared our results with the MG-RAST service for different datasets.

Conclusions: The MEGAN program now allows the interactive analysis and comparison of the taxonomical and functional content of multiple datasets. As a stand-alone tool, MEGAN provides an alternative to web portals for scientists that have concerns about uploading their unpublished data to a website.

Show MeSH
SEED-based functional assignment. Part of a SEED-based functional analysis of a marine metagenome sample. Each item represents a functional role in the SEED and is labeled by the number of reads assigned to this.
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Figure 1: SEED-based functional assignment. Part of a SEED-based functional analysis of a marine metagenome sample. Each item represents a functional role in the SEED and is labeled by the number of reads assigned to this.

Mentions: To perform a functional analysis, MEGAN assigns each read to the functional role of the highest scoring gene in a BLAST comparison against a protein database. Figure 1 shows a part of the functional analysis of a marine metagenome sample. The program reports the numbers of reads assigned to each functional role.


Functional analysis of metagenomes and metatranscriptomes using SEED and KEGG.

Mitra S, Rupek P, Richter DC, Urich T, Gilbert JA, Meyer F, Wilke A, Huson DH - BMC Bioinformatics (2011)

SEED-based functional assignment. Part of a SEED-based functional analysis of a marine metagenome sample. Each item represents a functional role in the SEED and is labeled by the number of reads assigned to this.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3044276&req=5

Figure 1: SEED-based functional assignment. Part of a SEED-based functional analysis of a marine metagenome sample. Each item represents a functional role in the SEED and is labeled by the number of reads assigned to this.
Mentions: To perform a functional analysis, MEGAN assigns each read to the functional role of the highest scoring gene in a BLAST comparison against a protein database. Figure 1 shows a part of the functional analysis of a marine metagenome sample. The program reports the numbers of reads assigned to each functional role.

Bottom Line: We have compared our results with the MG-RAST service for different datasets.The MEGAN program now allows the interactive analysis and comparison of the taxonomical and functional content of multiple datasets.As a stand-alone tool, MEGAN provides an alternative to web portals for scientists that have concerns about uploading their unpublished data to a website.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Bioinformatics ZBIT, Tübingen University, Sand 14, 72076 Tübingen, Germany. mitra@informatik.uni-tuebingen.de.

ABSTRACT

Background: Metagenomics is the study of microbial organisms using sequencing applied directly to environmental samples. Technological advances in next-generation sequencing methods are fueling a rapid increase in the number and scope of metagenome projects. While metagenomics provides information on the gene content, metatranscriptomics aims at understanding gene expression patterns in microbial communities. The initial computational analysis of a metagenome or metatranscriptome addresses three questions: (1) Who is out there? (2) What are they doing? and (3) How do different datasets compare? There is a need for new computational tools to answer these questions. In 2007, the program MEGAN (MEtaGenome ANalyzer) was released, as a standalone interactive tool for analyzing the taxonomic content of a single metagenome dataset. The program has subsequently been extended to support comparative analyses of multiple datasets.

Results: The focus of this paper is to report on new features of MEGAN that allow the functional analysis of multiple metagenomes (and metatranscriptomes) based on the SEED hierarchy and KEGG pathways. We have compared our results with the MG-RAST service for different datasets.

Conclusions: The MEGAN program now allows the interactive analysis and comparison of the taxonomical and functional content of multiple datasets. As a stand-alone tool, MEGAN provides an alternative to web portals for scientists that have concerns about uploading their unpublished data to a website.

Show MeSH