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:

Praveen Kumar avatar Praveen KumarNatalie Whitaker-Allen avatar Natalie Whitaker-AllenWillem de Koning avatar Willem de Koningorcid logoSantino Faack avatar Santino Faackorcid logoNikos Pechlivanis avatar Nikos Pechlivanisorcid logoDave Clements avatar Dave ClementsEmma Leith avatar Emma Leithorcid logoGiuseppe Defazio avatar Giuseppe DefazioDidier Debroas avatar Didier Debroasorcid logoDaniel Blankenberg avatar Daniel BlankenbergKatherine Do avatar Katherine Doorcid logoBérénice Batut avatar Bérénice Batutorcid logoHelena Rasche avatar Helena Rascheorcid logoLinelle Abueg avatar Linelle AbuegSophia Hampe avatar Sophia Hampeorcid logoArmin Dadras avatar Armin Dadrasorcid logoDeepti Varshney avatar Deepti Varshneyorcid logoFabio Cumbo avatar Fabio Cumboorcid logoNicola Soranzo avatar Nicola Soranzoorcid logoNadia Goué avatar Nadia Gouéorcid logoEngy Nasr avatar Engy NasrMatthias Bernt avatar Matthias BerntTarnima Omara avatar Tarnima Omaraorcid logoTristan Reynolds avatar Tristan Reynoldsorcid logoTimothy J. Griffin avatar Timothy J. GriffinDechen Bhuming avatar Dechen Bhumingorcid logoBjörn Grüning avatar Björn Grüningorcid logoCristóbal Gallardo avatar Cristóbal Gallardoorcid logoSubina Mehta avatar Subina MehtaSiyu Chen avatar Siyu Chenorcid logoWolfgang Maier avatar Wolfgang MaierBethan Manley avatar Bethan ManleyRay Sajulga avatar Ray Sajulgaorcid logoPaul Zierep avatar Paul ZierepIgor Makunin avatar Igor MakuninSujai Kumar avatar Sujai Kumarorcid logoVini Salazar avatar Vini SalazarNuwan Goonasekera avatar Nuwan Goonasekeraorcid logoRand Zoabi avatar Rand Zoabiorcid logoBert Droesbeke avatar Bert DroesbekeWilliam Durand avatar William Durandorcid logoAnna Syme avatar Anna SymeNiall Beard avatar Niall Beardorcid logoPolina Polunina avatar Polina PoluninaChristine Oger avatar Christine Ogerorcid logoHans-Rudolf Hotz avatar Hans-Rudolf HotzMichael Thang avatar Michael Thangorcid logoClea Siguret avatar Clea Siguretorcid logoPratik Jagtap avatar Pratik Jagtaporcid logoFotis E. Psomopoulos avatar Fotis E. Psomopoulosorcid logoMina Hojat Ansari avatar Mina Hojat Ansariorcid logoSaskia Hiltemann avatar Saskia Hiltemannorcid logoTeresa Müller avatar Teresa Müller

Funding

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

References