Training material for proteomics workflows in GalaxyYou can view the tutorial materials in different languages by clicking the dropdown icon next to the slides (slides) and tutorial (tutorial) buttons below.
Before diving into this topic, we recommend you to have a look at:
Start here if you are new to proteomic analysis in Galaxy.
Introduction to proteomics, protein identification, quantification and statistical modelling
Protein identification and quantification
These tutorials cover protein identification and/or label-free and label based quantification from data dependent acquisition (DDA) and data independent acquisition (DIA).
Postprocessing of proteomics data
These tutorial cover statistical analyses and visualizations after protein identification and quantification.
|Annotating a protein list identified by LC-MS/MS experiments|
|Biomarker candidate identification|
|Statistical analysis of DIA data|
Special proteomics techniques
These tutorials focus on special techniques such as N-terminomics and mass spectrometry imaging.
Detection and quantitation of N-termini (degradomics) via N-TAILS
|Mass spectrometry imaging: Loading and exploring MSI data|
These tutorials combine proteomics with other -omics technologies such as transcriptomics.
|Proteogenomics 1: Database Creation|
|Proteogenomics 2: Database Search|
|Proteogenomics 3: Novel peptide analysis|
|metaQuantome 1: Data creation|
|metaQuantome 2: Function|
|metaQuantome 3: Taxonomy|
Prediction of peptide properties
These tutorials explain in-silico analyses of different peptide properties.
|Machine Learning Modeling of Anticancer Peptides|
Peptide Library Data Analysis
You can use a public Galaxy instance which has been tested for the availability of the used tools. They are listed along with the tutorials above.
You can also use the following Docker image for these tutorials:
docker run -p 8080:80 quay.io/galaxy/proteomics-training
NOTE: Use the -d flag at the end of the command if you want to automatically download all the data-libraries into the container.
It will launch a flavored Galaxy instance available on http://localhost:8080. This instance will contain all the tools and workflows to follow the tutorials in this topic. Login as admin with password password to access everything.
Frequently Asked QuestionsCommon 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.
This material is reviewed by our Editorial Board:Melanie FöllSubina MehtaPratik JagtapBjörn Grüning
For any question related to this topic and the content, you can contact them or visit our Gitter channel.
This material was contributed to by:Ray SajulgaValentin LouxKlemens FröhlichFlorian Christoph SiglochJayadev JoshiTimothy J. GriffinPraveen KumarClemens BlankBjörn GrüningPratik JagtapMarie CraneMatthias FahrnerDaniel BlankenbergYves VandenbrouckMelanie FöllFlorence CombesJames JohnsonEmma LeithDavid ChristianySubina Mehta
This material was funded by:
- Kumar D, Yadav AK and Dash D: Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data.
Vaudel M, et al.: Shedding light on black boxes in protein identification.
An extensive tutorial for peptide and protein identification, available at http://compomics.com/bioinformatics-for-proteomics. The material is completely based on freely available and open-source tools.
Cappadona S, et al.: Current challenges in software solutions for mass spectrometry-based quantitative proteomics
A comprehensive review of current quantitative techniques, their advantages and pitfalls.
Tholen S, et al.: Limited and Degradative Proteolysis in the Context of Posttranslational Regulatory Networks: Current Technical and Conceptional Advances
Review on LC-MS/MS based proteomic methods to identify neo-N-termini, e.g. generated by protease cleavage.