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:

Dechen Bhuming avatar Dechen BhumingBethan Manley avatar Bethan Manleyorcid logoBjörn Grüning avatar Björn Grüningorcid logoNicola Soranzo avatar Nicola Soranzoorcid logoPaul Zierep avatar Paul ZierepPraveen Kumar avatar Praveen KumarIgor Makunin avatar Igor Makuninorcid logoPolina Polunina avatar Polina PoluninaSophia Hampe avatar Sophia HampeWilliam Durand avatar William Durandorcid logoTeresa Müller avatar Teresa MüllerSiyu Chen avatar Siyu Chenorcid logoRand Zoabi avatar Rand Zoabiorcid logoTimothy J. Griffin avatar Timothy J. Griffinorcid logoCristóbal Gallardo avatar Cristóbal Gallardoorcid logoMina Hojat Ansari avatar Mina Hojat AnsariSujai Kumar avatar Sujai KumarKatherine Do avatar Katherine Doorcid logoHans-Rudolf Hotz avatar Hans-Rudolf Hotzorcid logoDave Clements avatar Dave Clementsorcid logoHelena Rasche avatar Helena RascheRay Sajulga avatar Ray Sajulgaorcid logoClea Siguret avatar Clea Siguretorcid logoEngy Nasr avatar Engy Nasrorcid logoSaskia Hiltemann avatar Saskia Hiltemannorcid logoNikos Pechlivanis avatar Nikos PechlivanisChristine Oger avatar Christine OgerMatthias Bernt avatar Matthias BerntNuwan Goonasekera avatar Nuwan GoonasekeraNiall Beard avatar Niall BeardMichael Thang avatar Michael Thangorcid logoNadia Goué avatar Nadia GouéDidier Debroas avatar Didier Debroasorcid logoDeepti Varshney avatar Deepti VarshneyEmma Leith avatar Emma Leithorcid logoTristan Reynolds avatar Tristan Reynoldsorcid logoFabio Cumbo avatar Fabio Cumboorcid logoPratik Jagtap avatar Pratik Jagtaporcid logoBérénice Batut avatar Bérénice Batutorcid logoLinelle Abueg avatar Linelle Abuegorcid logoBert Droesbeke avatar Bert DroesbekeTarnima Omara avatar Tarnima Omaraorcid logoVini Salazar avatar Vini Salazarorcid logoAnna Syme avatar Anna SymeSantino Faack avatar Santino Faackorcid logoFotis E. Psomopoulos avatar Fotis E. PsomopoulosWillem de Koning avatar Willem de Koningorcid logoWolfgang Maier avatar Wolfgang Maierorcid logoSubina Mehta avatar Subina Mehtaorcid logoDaniel Blankenberg avatar Daniel Blankenberg

Funding

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

References