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

Before diving into this topic, we recommend you to have a look at:

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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
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
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
Remove contamination and host reads

Frequently Asked Questions

Common questions regarding this topic have been collected on a dedicated FAQ page . Common questions related to specific tutorials can be accessed from the tutorials themselves.

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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:

Niall Beard avatar Niall BeardMatthias Bernt avatar Matthias Berntorcid logoCristóbal Gallardo avatar Cristóbal GallardoTarnima Omara avatar Tarnima OmaraMichael Thang avatar Michael ThangRay Sajulga avatar Ray Sajulgaorcid logoLinelle Abueg avatar Linelle Abuegorcid logoAnna Syme avatar Anna Symeorcid logoFabio Cumbo avatar Fabio Cumboorcid logoDaniel Blankenberg avatar Daniel Blankenbergorcid logoMina Hojat Ansari avatar Mina Hojat Ansariorcid logoVini Salazar avatar Vini SalazarNuwan Goonasekera avatar Nuwan GoonasekeraEmma Leith avatar Emma Leithorcid logoHelena Rasche avatar Helena Rascheorcid logoPaul Zierep avatar Paul Ziereporcid logoDeepti Varshney avatar Deepti Varshneyorcid logoTristan Reynolds avatar Tristan ReynoldsIgor Makunin avatar Igor Makuninorcid logoRand Zoabi avatar Rand ZoabiBethan Manley avatar Bethan Manleyorcid logoBjörn Grüning avatar Björn Grüningorcid logoNadia Goué avatar Nadia Gouéorcid logoBérénice Batut avatar Bérénice Batutorcid logoPolina Polunina avatar Polina Poluninaorcid logoSubina Mehta avatar Subina Mehtaorcid logoHans-Rudolf Hotz avatar Hans-Rudolf HotzDidier Debroas avatar Didier Debroasorcid logoTeresa Müller avatar Teresa Müllerorcid logoTimothy J. Griffin avatar Timothy J. Griffinorcid logoPratik Jagtap avatar Pratik JagtapSiyu Chen avatar Siyu Chenorcid logoNikos Pechlivanis avatar Nikos Pechlivanisorcid logoEngy Nasr avatar Engy NasrSantino Faack avatar Santino Faackorcid logoFotis E. Psomopoulos avatar Fotis E. PsomopoulosChristine Oger avatar Christine Ogerorcid logoBert Droesbeke avatar Bert DroesbekeSophia Hampe avatar Sophia HampeSujai Kumar avatar Sujai KumarWilliam Durand avatar William Durandorcid logoNicola Soranzo avatar Nicola Soranzoorcid logoDave Clements avatar Dave ClementsDechen Bhuming avatar Dechen BhumingWillem de Koning avatar Willem de Koningorcid logoSaskia Hiltemann avatar Saskia HiltemannPraveen Kumar avatar Praveen Kumarorcid logoWolfgang Maier avatar Wolfgang Maierorcid logoClea Siguret avatar Clea SiguretKatherine Do avatar Katherine Do

Funding

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

References