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
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

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:

William Durand avatar William Durandorcid logoBert Droesbeke avatar Bert DroesbekeNuwan Goonasekera avatar Nuwan Goonasekeraorcid logoTristan Reynolds avatar Tristan Reynoldsorcid logoGiuseppe Defazio avatar Giuseppe Defazioorcid logoDave Clements avatar Dave Clementsorcid logoDaniel Blankenberg avatar Daniel Blankenbergorcid logoCristóbal Gallardo avatar Cristóbal GallardoNatalie Whitaker-Allen avatar Natalie Whitaker-AllenPraveen Kumar avatar Praveen Kumarorcid logoFotis E. Psomopoulos avatar Fotis E. PsomopoulosEmma Leith avatar Emma Leithorcid logoTeresa Müller avatar Teresa Müllerorcid logoNikos Pechlivanis avatar Nikos PechlivanisIgor Makunin avatar Igor MakuninBethan Manley avatar Bethan ManleyWillem de Koning avatar Willem de Koningorcid logoBérénice Batut avatar Bérénice Batutorcid logoDeepti Varshney avatar Deepti Varshneyorcid logoPaul Zierep avatar Paul Ziereporcid logoHans-Rudolf Hotz avatar Hans-Rudolf Hotzorcid logoWolfgang Maier avatar Wolfgang Maierorcid logoBjörn Grüning avatar Björn GrüningTarnima Omara avatar Tarnima Omaraorcid logoSubina Mehta avatar Subina MehtaMatthias Bernt avatar Matthias Berntorcid logoNicola Soranzo avatar Nicola Soranzoorcid logoSantino Faack avatar Santino Faackorcid logoFabio Cumbo avatar Fabio Cumboorcid logoHelena Rasche avatar Helena Rascheorcid logoArmin Dadras avatar Armin DadrasMichael Thang avatar Michael Thangorcid logoNadia Goué avatar Nadia GouéRay Sajulga avatar Ray Sajulgaorcid logoPolina Polunina avatar Polina PoluninaSiyu Chen avatar Siyu Chenorcid logoSaskia Hiltemann avatar Saskia HiltemannKatherine Do avatar Katherine Doorcid logoClea Siguret avatar Clea Siguretorcid logoPratik Jagtap avatar Pratik Jagtaporcid logoRand Zoabi avatar Rand Zoabiorcid logoAnna Syme avatar Anna SymeSophia Hampe avatar Sophia HampeNiall Beard avatar Niall BeardDechen Bhuming avatar Dechen BhumingSujai Kumar avatar Sujai Kumarorcid logoEngy Nasr avatar Engy Nasrorcid logoMina Hojat Ansari avatar Mina Hojat AnsariChristine Oger avatar Christine Ogerorcid logoLinelle Abueg avatar Linelle Abuegorcid logoTimothy J. Griffin avatar Timothy J. GriffinDidier Debroas avatar Didier Debroasorcid logoVini Salazar avatar Vini Salazar

Funding

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

References