Microbiome

A microbiome is the community of microorganisms that can usually be found living together in any given habitat. Microbiome research has grown substantially over the past decade in terms of the range of biomes sampled, identified taxa, and the volume of data derived from the samples.

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Requirements

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Material

You can view the tutorial materials in different languages by clicking the dropdown icon next to the slides (slides) and tutorial (tutorial) buttons below.

Introduction

Start here if you are new to microbiome analyses in Galaxy.

Lesson Slides Hands-on Recordings Input dataset Workflows
Introduction to Microbiome Analysis
Analyses of metagenomics data - The global picture

Metabarcoding / Amplicon analyses

Taxonomic characterisation of mixed samples using a single gene region.

Lesson Slides Hands-on Recordings Input dataset Workflows
16S Microbial analysis with Nanopore data
Antibiotic resistance detection
Building an amplicon sequence variant (ASV) table from 16S data using DADA2
MGnify v5.0 Amplicon Pipeline
QIIME 2 Cancer Microbiome Intervention external-link
QIIME 2 Moving Pictures external-link
16S Microbial Analysis with mothur (extended)
16S Microbial Analysis with mothur (short)

Metagenomics

Taxonomic and functional characterisation and assembly of mixed samples using whole genome data.

Lesson Slides Hands-on Recordings Input dataset Workflows
Assembly of metagenomic sequencing data
Binning of metagenomic sequencing data
Building and Annotating Metagenome-Assembled Genomes (MAGs) from Short Metagenomics Paired Reads
Calculating α and β diversity from microbiome taxonomic data
Detection of shared microbial strains with SameStr
Identification of the micro-organisms in a beer using Nanopore sequencing
Indexing and profiling microbes with MetaSBT
Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition
Remove contamination and host reads
Taxonomic Profiling and Visualization of Metagenomic Data

Metatranscriptomics

Taxonomic and functional characterisation of mixed samples using transcriptome data.

Lesson Slides Hands-on Recordings Input dataset Workflows
Metatranscriptomics analysis using microbiome RNA-seq data
Metatranscriptomics analysis using microbiome RNA-seq data (short)

Metaproteomics

These tutorials are step by step analysis from database generation to the discovery of peptides to verification, quantitation, and interpretation of the results.

Lesson Slides Hands-on Recordings Input dataset Workflows
Clinical Metaproteomics 1: Database-Generation
Clinical Metaproteomics 2: Discovery
Clinical Metaproteomics 3: Verification
Clinical Metaproteomics 4: Quantitation
Clinical Metaproteomics 5: Data Interpretation

Other

Assorted Tutorials

Lesson Slides Hands-on Recordings Input dataset Workflows
Identifying Mycorrhizal Fungi from ITS2 sequencing using LotuS2
Query an annotated mobile genetic element database to identify and annotate genetic elements (e.g. plasmids) in metagenomics data

Learning Pathways

Or have a look at one of our learning pathways involving this topic. Learning pathways are sets of tutorials curated for you by community experts to form a coherent set of lessons around a topic, building up knowledge as you go. We always recommend to follow the tutorials in the order they are listed in the pathway.

Frequently Asked Questions

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Editorial Board

This material is reviewed by our Editorial Board:

orcid logoBérénice Batut avatar Bérénice Batutorcid logoSaskia Hiltemann avatar Saskia Hiltemannorcid logoPaul Zierep avatar Paul Zierep

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Contributors

This material was contributed to by:

orcid logoWolfgang Maier avatar Wolfgang Maierorcid logoDaniel Blankenberg avatar Daniel BlankenbergKatherine Do avatar Katherine DoMichael Thang avatar Michael Thangorcid logoBjörn Grüning avatar Björn Grüningorcid logoGiuseppe Defazio avatar Giuseppe Defazioorcid logoLinelle Abueg avatar Linelle Abuegorcid logoArmin Dadras avatar Armin Dadrasorcid logoPaul Zierep avatar Paul Ziereporcid logoTimothy J. Griffin avatar Timothy J. Griffinorcid logoVini Salazar avatar Vini Salazarorcid logoFotis E. Psomopoulos avatar Fotis E. Psomopoulosorcid logoSantino Faack avatar Santino Faackorcid logoCristóbal Gallardo avatar Cristóbal GallardoIgor Makunin avatar Igor Makuninorcid logoBérénice Batut avatar Bérénice BatutChristine Oger avatar Christine OgerWilliam Durand avatar William DurandSiyu Chen avatar Siyu Chenorcid logoHelena Rasche avatar Helena RascheNiall Beard avatar Niall Beardorcid logoClea Siguret avatar Clea Siguretorcid logoTristan Reynolds avatar Tristan Reynoldsorcid logoDave Clements avatar Dave ClementsDechen Bhuming avatar Dechen Bhumingorcid logoNicola Soranzo avatar Nicola Soranzoorcid logoMatthias Bernt avatar Matthias BerntEmma Leith avatar Emma Leithorcid logoPratik Jagtap avatar Pratik Jagtaporcid logoRand Zoabi avatar Rand Zoabiorcid logoAnna Syme avatar Anna SymeTarnima Omara avatar Tarnima Omaraorcid logoMina Hojat Ansari avatar Mina Hojat Ansariorcid logoTeresa Müller avatar Teresa Müllerorcid logoSubina Mehta avatar Subina Mehtaorcid logoDeepti Varshney avatar Deepti VarshneyWillem de Koning avatar Willem de Koningorcid logoHans-Rudolf Hotz avatar Hans-Rudolf Hotzorcid logoFabio Cumbo avatar Fabio CumboNatalie Whitaker-Allen avatar Natalie Whitaker-AllenNuwan Goonasekera avatar Nuwan Goonasekeraorcid logoNikos Pechlivanis avatar Nikos Pechlivanisorcid logoXenia Morera Martínez avatar Xenia Morera MartínezSujai Kumar avatar Sujai Kumarorcid logoEngy Nasr avatar Engy NasrRay Sajulga avatar Ray SajulgaPraveen Kumar avatar Praveen Kumarorcid logoBert Droesbeke avatar Bert Droesbekeorcid logoNadia Goué avatar Nadia Gouéorcid logoPolina Polunina avatar Polina PoluninaSophia Hampe avatar Sophia Hampeorcid logoSaskia Hiltemann avatar Saskia HiltemannBethan Manley avatar Bethan ManleyDidier Debroas avatar Didier Debroas

Funding

These individuals or organisations provided funding support for the development of this resource

References