Microbiome Analysis Tools Developed at EMBL
Welcome to the web portal for computational microbiome analysis tools developed at EMBL by the groups of Peer Bork and Georg Zeller. The graph illustrates which analysis tasks can be performed by each of the tools listed to the right and how they can be combined into complex microbiome analysis pipelines. Find out more about the tools by expanding the corresponding list items. Tags indicating application areas show you which tools are applicable to the analysis of 16S amplicon sequencing data or prokaryotic genome sequencing data in addition to shotgun metagenomics data.

MOCAT
Metagenomics assembly and profiling pipeline
MOCAT is a modular and scalable software pipeline for analyzing shotgun metagenomics datasets generated with Illumina technology. Starting from raw fastQ files, it can quality-filter and remove contaminants from them, assemble metagenomic reads into contigs, predict prokaryotic genes on these, identify phylogenetic marker genes and generate taxonomic abundance profiles by mapping reads to these marker genes.

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Version: 2.0

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Publications:

Kultima et al. MOCAT2: a metagenomic assembly, annotation and profiling framework. Bioinformatics 16. 2016. PMID: 27153620

Kultima et al. MOCAT: a metagenomics assembly and gene prediction toolkit. PLoS ONE 10. 2012. PMID: 23082188



Metagenomics



SpecI
Molecular deliniation of prokaryotic species
SpecI is a species identification tool using genomic sequences to delineate prokaryotic species. It facilitates fast, accurate and automated taxonomic assignments of newly sequenced genomes based on comparisons of 40 universal, single-copy phylogenetic marker genes extracted from a comprehensive database of sequenced prokaryotic genomes.

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Version: 1.0

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Publications:

Mende et al. Accurate and universal delineation of prokaryotic species. Nat. Methods 9. 2013. PMID: 23892899



Metagenomics
Genomics



mOTUs
Metagenomic species profiling
Metagenomic operational taxonomic units (mOTUs) allow for the taxonomic profiling of known (sequenced) and unknown microorganisms at species-level resolution from shotgun sequencing data. The method clusters single-copy phylogenetic marker gene sequences from metagenomes and reference genomes into mOTUs to quantify their abundances in shotgun metagenomic samples.

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Version: 1.0

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Publications:

Sunagawa et al. Metagenomic species profiling using universal phylogenetic marker genes. Nat. Methods 12. 2013. PMID: 24141494



Metagenomics



eggNOG
Resource for orthologous genes
eggNOG is a database of nested orthologous gene groups (NOGs) infered using unsupervised clustering applied to >2,000 complete genomes followed by comprehensive characterization and analysis of the resulting gene families. eggNOG provides orthologous group assignments at >100 different taxonomic levels as well as multiple sequence alignments, maximum-likelihood trees and broad functional annotations for each group accessible via a web interface or through bulk download.

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Publications:

Huerta-Cepas et al. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. D1. 2016. PMID: 26582926

Powell et al. eggNOG v4.0: nested orthology inference across 3686 organisms. Nucleic Acids Res. Database issue. 2014. PMID: 24297252

Powell et al. eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges. Nucleic Acids Res. Database issue. 2012. PMID: 22096231

Muller et al. eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations. Nucleic Acids Res. Database issue. 2010. PMID: 19900971

Jensen et al. eggNOG: automated construction and annotation of orthologous groups of genes. Nucleic Acids Res. Database issue. 2008. PMID: 17942413



Metagenomics
Genomics



iPATH
Cellular pathway mapping tool
iPath is a web-based tool for the visualization and analysis of cellular pathways. Based on functional annotations (such as KEGG), it provides pathway maps for primary cellular metabolism as well as for some additional secondary metabolite synthesis and regulatory pathways. Users can map their own data onto these pathway maps. Due to its navigation and customization functions, iPATH thus allows users to easily explore and analyze the functional and metabolic capabilities of their (meta-)genomic data sets.

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Publications:

Yamada et al. iPath2.0: interactive pathway explorer. Nucleic Acids Res. Web Server issue. 2011. PMID: 21546551

Letunic et al. iPath: interactive exploration of biochemical pathways and networks. Trends Biochem. Sci. 3. 2008. PMID: 18276143



Metagenomics
Genomics



Interactive Tree Of Life (iTOL)
Interactive tree visualization
Interactive Tree Of Life (iTOL) is an online tool for the display and manipulation of phylogenetic trees. It provides a large variety of tree layouts, drawing and annotation features including circular tree layout, which is well-suited particularly for mid-sized trees (up to several thousand leaves). Tree displays can be exported in several graphical formats, both bitmap and vector based.

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Version: 3.0

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Publications:

Letunic & Bork Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. W1. 2016. PMID: 27095192

Letunic & Bork Interactive Tree Of Life v2: online annotation and display of phylogenetic trees made easy. Nucleic Acids Res. Web Server issue. 2011. PMID: 21470960

Letunic & Bork Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics 1. 2007. PMID: 17050570



Phylogenetics
Metagenomics
Genomics



Enterotyping
Gut microbial community typing
Enterotypes are densely populated regions in a high-dimensional space of microbiome community composition, by which human individuals can be stratified (Arumugam, Raes et al. Nature 2011). Computational methods to detect and characterise enterotypes in any dataset, either to reproduce previous reports or determine enterotypes in new studies, are provided and explained.

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Version: 1.0

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Publications:

Arumugam et al. Enterotypes of the human gut microbiome. Nature 7346. 2011. PMID: 21508958



Metagenomics



SIAMCAT
Statistical analysis of microbiome data
SIAMCAT is a modular framework for the statistical inference of associations between microbial communities and host phenotypes, such as disease states in clinical case-control studies. SIAMCAT is based on LASSO models, which offer distinctive advantages for model interpretation and microbial biomarker selection and avoid overfitting issues that can arise in naive combinations of feature selection and cross-validation.

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Metagenomics
Genomics
Statistics and probability



For questions & feedback, please contact Peer Bork or Georg Zeller