Proteomics — Editorial Board Home

This is a new, experimental "Editorial Board Home" for a given topic. It is intended to provide a single place for maintainers and editorial board members to find out key information about their topic and identify action items.

Editorial Board

orcid logoSubina Mehta avatar Subina Mehtaorcid logoPratik Jagtap avatar Pratik Jagtaporcid logoBjörn Grüning avatar Björn Grüningorcid logoMelanie Föll avatar Melanie Föll

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Topic Materials

Material Contributions v2 Pre-requisites Follow up trainings Data on Zenodo Notebook Server Compatibility
Introduction to proteomics, protein identification, quantification and statistical modelling ❌ ✅
DIA Analysis using OpenSwathWorkflow ❌ ✅ ✅
EncyclopeDIA ❌ ✅
Label-free data analysis using MaxQuant ❌ ✅
Label-free versus Labelled - How to Choose Your Quantitation Method ❌ ❌
Library Generation for DIA Analysis ❌ ✅
MaxQuant and MSstats for the analysis of TMT data ❌ ✅
MaxQuant and MSstats for the analysis of label-free data ❌ ✅ ❌
Peptide and Protein ID using OpenMS tools ❌ ✅ ✅ ✅
Peptide and Protein ID using SearchGUI and PeptideShaker ❌ ✅
Peptide and Protein Quantification via Stable Isotope Labelling (SIL) ❌ ✅ ✅
Protein FASTA Database Handling ❌ ❌
Annotating a protein list identified by LC-MS/MS experiments ❌ ✅
Biomarker candidate identification ❌ ❌
Secretome Prediction ❌ ✅
Single Cell Proteomics data analysis with bioconductor-scp ✅ ✅
Statistical analysis of DIA data ❌ ✅ ✅
Detection and quantitation of N-termini (degradomics) via N-TAILS ❌ ❌
Mass spectrometry imaging: Loading and exploring MSI data ❌ ✅
Metaproteomics tutorial ❌ ✅
Multiomics data analysis using MultiGSEA ✅ ✅
Proteogenomics 1: Database Creation ❌ ✅ ✅
Proteogenomics 2: Database Search ❌ ✅ ✅ ✅
Proteogenomics 3: Novel peptide analysis ❌ ✅ ✅
metaQuantome 1: Data creation ❌ ✅ ✅
metaQuantome 2: Function ❌ ✅ ✅ ✅
metaQuantome 3: Taxonomy ❌ ✅ ✅ ✅
Machine Learning Modeling of Anticancer Peptides ❌ ✅
Peptide Library Data Analysis ❌ ✅
Clinical Metaproteomics 1: Database-Generation ✅ ✅ ✅ ✅
Clinical Metaproteomics 2: Discovery ✅ ✅ ✅ ✅
Clinical Metaproteomics 3: Verification ✅ ✅ ✅ ✅
Clinical Metaproteomics 4: Quantitation ✅ ✅ ✅ ✅
Clinical Metaproteomics 5: Data Interpretation ✅ ✅ ✅ ✅
Neoantigen 1: Fusion-Database-Generation ✅ ✅ ✅ ✅
Neoantigen 2: Non-Reference-Database-Generation ✅ ✅ ✅ ✅
Neoantigen 3: Database merge and FragPipe discovery ✅ ✅ ✅ ✅
Neoantigen 4: PepQuery2 Verification ✅ ✅ ✅ ✅
Neoantigen 5: Variant Annotation ✅ ✅ ✅ ✅
Neoantigen 6: Predicting HLA Binding ✅ ✅ ✅ ✅
Neoantigen 7: IEDB binding PepQuery Validated Neopeptides ✅ ✅ ✅

Topic Workflows

Material Workflow Updated Version Tests Reports Comments
DIA Analysis using OpenSwathWorkflow DIA_Analysis_OSW Apr 3, 2025 1 ❌ ❌ ❌
EncyclopeDIA EncyclopeDIA-GTN Apr 3, 2025 2 ✅ ✅ ❌
Label-free data analysis using MaxQuant Proteomics: MaxQuant workflow Apr 3, 2025 6 ✅ ❌ ❌
Library Generation for DIA Analysis DIA_lib_OSW Apr 3, 2025 1 ❌ ❌ ❌
MaxQuant and MSstats for the analysis of TMT data MaxQuant MSstatsTMT Training Apr 3, 2025 1 ❌ ❌ ❌
MaxQuant and MSstats for the analysis of label-free data Proteomics: MaxQuant and MSstats LFQ workflow Apr 3, 2025 3 ❌ ❌ ❌
Peptide and Protein ID using OpenMS tools Proteomics: Peptide and Protein ID using OpenMS Apr 3, 2025 6 ❌ ❌ ❌
Peptide and Protein ID using OpenMS tools Peptide And Protein ID Via OMS Using Two Search Engines Apr 3, 2025 4 ❌ ❌ ❌
Peptide and Protein ID using SearchGUI and PeptideShaker Peptide And Protein ID Tutorial Apr 3, 2025 4 ❌ ❌ ❌
Peptide and Protein ID using SearchGUI and PeptideShaker ProteinID SG PS Tutorial WF datasetCollection Apr 3, 2025 4 ❌ ❌ ❌
Peptide and Protein Quantification via Stable Isotope Labelling (SIL) Proteomics: Peptide and Protein Quantification via stable istobe labeling Apr 3, 2025 7 ✅ ❌ ❌
Protein FASTA Database Handling Proteomics: database handling Apr 3, 2025 5 ❌ ❌ ❌
Protein FASTA Database Handling Proteomics: database handling including mycoplasma Apr 3, 2025 6 ❌ ❌ ❌
Annotating a protein list identified by LC-MS/MS experiments 'Proteome Annotation' Apr 3, 2025 3 ❌ ❌ ❌
Annotating a protein list identified by LC-MS/MS experiments ProteoRE ProteomeAnnotation Tutorial (release 2.0) Apr 3, 2025 4 ❌ ❌ ❌
Biomarker candidate identification 'Biomarkers4Paris' Workflow Apr 3, 2025 3 ❌ ❌ ❌
Secretome Prediction Secreted Proteins Via GO Annotation And WoLF PSORT For shCTSB Paper Apr 3, 2025 3 ❌ ❌ ❌
Statistical analysis of DIA data DIA_analysis_MSstats Apr 3, 2025 2 ✅ ❌ ❌
Statistical analysis of DIA data DIA_analysis_MSstats Apr 3, 2025 2 ✅ ❌ ❌
Detection and quantitation of N-termini (degradomics) via N-TAILS Tails Triple Dimethyl OpenMS2.1 Apr 3, 2025 4 ❌ ❌ ❌
Mass spectrometry imaging: Loading and exploring MSI data MS Imaging Loading Exploring Data Apr 3, 2025 4 ❌ ❌ ❌
Metaproteomics tutorial Metaproteomics_GTN Apr 3, 2025 7 ❌ ❌ ❌
Multiomics data analysis using MultiGSEA MultiGSEA Apr 3, 2025 1 ✅ ✅ ❌
Proteogenomics 1: Database Creation GTN Proteogenomics1 Database Creation Apr 3, 2025 8 ❌ ❌ ❌
Proteogenomics 2: Database Search GTN Proteogemics2 Database Search Apr 3, 2025 7 ❌ ❌ ❌
Proteogenomics 3: Novel peptide analysis GTN Proteogemics3 Novel Peptide Analysis Apr 3, 2025 6 ❌ ❌ ❌
metaQuantome 1: Data creation metaQuantome_datacreation_workflow Apr 3, 2025 3 ✅ ❌ ❌
metaQuantome 2: Function metaquantome-function-worklow Apr 3, 2025 2 ❌ ❌ ❌
metaQuantome 3: Taxonomy metaquantome-taxonomy-workflow Apr 3, 2025 2 ❌ ❌ ❌
Machine Learning Modeling of Anticancer Peptides PeptideML Apr 3, 2025 1 ❌ ❌ ❌
Peptide Library Data Analysis Copy of PeptideDataAnalysis (imported from uploaded file) Apr 3, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 1: Database-Generation WF1_Database_Generation_Workflow Apr 3, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 2: Discovery WF2_Discovery-Workflow Apr 3, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 3: Verification WF3_VERIFICATION_WORKFLOW Apr 3, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 4: Quantitation WF4_Quantitation_Workflow Apr 3, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 5: Data Interpretation WF5_Data_Interpretation_Worklow Apr 3, 2025 1 ❌ ❌ ❌
Neoantigen 1: Fusion-Database-Generation Gigascience_Fusions_demonstration_STS26T-Gent_Workflow Apr 3, 2025 1 ❌ ✅ ❌
Neoantigen 2: Non-Reference-Database-Generation Gigascience_Indels_SAV_non-reference_demonstration_STS26T-Gent_Workflow Apr 3, 2025 1 ❌ ✅ ❌
Neoantigen 3: Database merge and FragPipe discovery GigaScience_Database_merge_FragPipe_STS26T_demonstration Apr 3, 2025 2 ❌ ✅ ❌
Neoantigen 4: PepQuery2 Verification GigaScience_PepQuery2_demonstration_STS26T_neoantigen_candidates_workflow Apr 3, 2025 1 ❌ ✅ ❌
Neoantigen 5: Variant Annotation GigaScience_Peptide_Annotation_demonstration_STS26T_neoantigen_candidates_workflow Apr 3, 2025 2 ❌ ✅ ❌
Neoantigen 6: Predicting HLA Binding GigaScience-RNAseq-Optitype-seq2HLA-to-IEDB-alleles Apr 3, 2025 1 ❌ ✅ ❌
Neoantigen 7: IEDB binding PepQuery Validated Neopeptides GigaScience-IEDB-PepQuery-Neoantigen Apr 3, 2025 1 ❌ ✅ ❌

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Learning Pathways using materials from this Topic

image of a 3D protein folding structure
Clinical metaproteomics workflows within Galaxy

This learning path aims to teach you the basics of how to perform metaproteomics analysis of the clinical data within the Galaxy platform. You will learn how to use Galaxy for analysis and will be guided through the most common first steps of any metaproteomics database generation to searching the database, verifying the proteins/peptides, and data analysis.

beginner proteomics
image of a 3D protein folding structure
Proteogenomics

This learning path aims to teach you the basics of how to perform proteogenomics analysis of the Mass spectrometry data within the Galaxy platform. You will learn how to use Galaxy for analysis and will be guided through the most common first steps of any proteogenomics database generation to searching the database, followed by novel peptide data analysis.

beginner proteomics
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Events using materials from this Topic

TODO once this is merged: https://github.com/galaxyproject/training-material/pull/4963

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