Module: Proteomics

This lecture will provide an introduction to mass spectrometry (MS) based proteomics analysis. Slides created by Melanie Föll.

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Modern mass spectrometry-based proteomics enables the identification and quantification of thousands of proteins. Therefore, quantitative mass spectrometry represents an indispensable technology for biological and clinical research. Statistical analyses are required for the unbiased answering of scientific questions and to uncover all important information in the proteomic data. In this training we will cover the full analysis workflow from label-free, data dependent acquisition (DDA) raw data to statistical results. We’ll use two popular quantitative proteomics software: MaxQuant and MSstats.

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• Learn how to use MaxQuant and MSstats for the analysis of label-free shotgun (DDA) data

In this tutorial, we will provide a walkthrough on how to generate a customized protein sequence database using RNA-Seq data. The resultant FASTA database contains sequences with single amino acid variants (SAVs), insertions and deletions (indels)and transcript assemblies (splicing variants). This database can then be used to identify protein sequence variants from the mass spectrometry data.

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• Generating a customized Protein sequence database with variants, indels, splice junctions and known sequences.

In this demonstration, we’re continuing the process of proteogenomic analysis. Here, we search mass spectrometry data against a custom proteogenomics FASTA database to create peptide spectral matches (PSMs) for each dataset; we also isolate non-canonical peptides from the resulting data for further analysis. If you would like to view the results yourself, we provide example histories in the FAQ document

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• A proteogenomic data analysis of mass spectrometry data to identify and visualize variant peptides.

In this demonstration, we will investigate the peptides that were identified during proteogenomics tutorial 2. We will identify the presence of novel proteoforms that are absent in the reference database, annotate the novel peptides and visualize them using the Multi-omics Visualization Platform (MVP). If you would like to view the results yourself, we provide example histories in the FAQ document

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• How to assign and visualize the genomic localization of these identified novel proteoforms?

This lecture will introduce EncyclopeDIA.

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This tutorial will walk you through an analysis with EncyclopeDIA step by step.

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• Understand the difference between DDA and DIA methods
• Performing quantitative analysis using DIA data
• Understand the purpose and benefits of using a Chromatogram Library for detection of peptides
• You can use Bloom's Taxonomy to write effective learning objectives

In this tutorial, the basic workflow for metaproteomics is described, which includes database search, seeking taxonomy information and functional analysis. Related metaproteomics and functional microbiome tools and GTN tutorials are also mentioned in this tutorial.

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• A taxonomy and functional analysis of metaproteomic mass spectrometry data.

This tutorial covers an annotation pipeline for a protein list identified by LC-MS/MS experiments.

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• Execute a complete annotation pipeline of a protein list identified by LC-MS/MS experiments

The Coronavirus Disease 2019 (COVID-19) global pandemic has had a profound, lasting impact on the world’s population. Accurate and timely diagnosis of COVID-19 infection is an important step for providing care and containing its further spread. In this tutorial, attendees will be introduced to two workflows – a) database search workflow and b) peptide validation workflow. Attendees of the workshop will get an in-depth knowledge of the Galaxy workflows that detect SARS-CoV-2 peptides (10.1186/s12014-021-09321-1)) and co-infecting pathogen peptides (10.1021/acs.jproteome.0c00822).

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