GigaScience_Peptide_Annotation_demonstration_STS26T_neoantigen_candidates_workflow
proteomics-neoantigen-5-variant-annotation/main-workflow
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flowchart TD 0["ℹ️ Input Dataset\nNovel_Peptides"]; style 0 stroke:#2c3143,stroke-width:4px; 1["ℹ️ Input Dataset\nFragpipe-Peptide-Report"]; style 1 stroke:#2c3143,stroke-width:4px; 2["ℹ️ Input Dataset\nAnnotated-GffCompared-GTFtoBED"]; style 2 stroke:#2c3143,stroke-width:4px; 3["ℹ️ Input Dataset\nHomo_sapiens.GRCh38_canon.106.gtf"]; style 3 stroke:#2c3143,stroke-width:4px; 4["Peptide_to_Protein_Annotation"]; 0 -->|output| 4; 1 -->|output| 4; 4631011c-b1d4-4964-96d6-5a11201afb75["Output\nPeptide_to_Protein_Annotation"]; 4 --> 4631011c-b1d4-4964-96d6-5a11201afb75; style 4631011c-b1d4-4964-96d6-5a11201afb75 stroke:#2c3143,stroke-width:4px; 5["FASTA-IEDB"]; 4 -->|output| 5; 3b728452-3d59-4e5f-a9dc-8764ceb60094["Output\nFASTA-IEDB"]; 5 --> 3b728452-3d59-4e5f-a9dc-8764ceb60094; style 3b728452-3d59-4e5f-a9dc-8764ceb60094 stroke:#2c3143,stroke-width:4px; 6["Converting_pipes_to_columns"]; 4 -->|output| 6; 58ea288e-1160-4617-8207-453bf29b0d12["Output\nTable-processing-1"]; 6 --> 58ea288e-1160-4617-8207-453bf29b0d12; style 58ea288e-1160-4617-8207-453bf29b0d12 stroke:#2c3143,stroke-width:4px; 7["Modifying-string-name"]; 6 -->|out_file1| 7; a607fb3f-2e87-410a-9dfb-9286baf667e9["Output\nModified-string-name"]; 7 --> a607fb3f-2e87-410a-9dfb-9286baf667e9; style a607fb3f-2e87-410a-9dfb-9286baf667e9 stroke:#2c3143,stroke-width:4px; 8["Converting_colons_to_columns"]; 7 -->|out_file1| 8; e24ff14e-b512-4444-9abb-b3c46d4fb707["Output\nTable-processing-2"]; 8 --> e24ff14e-b512-4444-9abb-b3c46d4fb707; style e24ff14e-b512-4444-9abb-b3c46d4fb707 stroke:#2c3143,stroke-width:4px; 9["Extracting-info-from-GFFtobed"]; 8 -->|out_file1| 9; 2 -->|output| 9; e78166a9-a99b-429d-b01e-e5e19084e1c0["Output\nExtracting-info-from-GFFtobed"]; 9 --> e78166a9-a99b-429d-b01e-e5e19084e1c0; style e78166a9-a99b-429d-b01e-e5e19084e1c0 stroke:#2c3143,stroke-width:4px; 10["Table-processing-3"]; 9 -->|output| 10; 734962f8-efbf-4b30-a00b-0293b098eb68["Output\nTable-processing-3"]; 10 --> 734962f8-efbf-4b30-a00b-0293b098eb68; style 734962f8-efbf-4b30-a00b-0293b098eb68 stroke:#2c3143,stroke-width:4px; 11["Peptide-location-generation"]; 10 -->|output| 11; 0d9f1cbf-fa72-42c1-ab78-4faa5e123bb1["Output\nPeptide-location-generation"]; 11 --> 0d9f1cbf-fa72-42c1-ab78-4faa5e123bb1; style 0d9f1cbf-fa72-42c1-ab78-4faa5e123bb1 stroke:#2c3143,stroke-width:4px; 12["BED-File-for-PepPointer"]; 11 -->|output| 12; 3970ec24-eb99-459f-8bb4-bc3b69faaca9["Output\nBED-File-for-PepPointer"]; 12 --> 3970ec24-eb99-459f-8bb4-bc3b69faaca9; style 3970ec24-eb99-459f-8bb4-bc3b69faaca9 stroke:#2c3143,stroke-width:4px; 13["PepPointer"]; 12 -->|output| 13; 3 -->|output| 13; ee5ad6db-d9d4-4ae4-9d69-c37ccb3f4475["Output\nPepPointer-Annotated-Peptides"]; 13 --> ee5ad6db-d9d4-4ae4-9d69-c37ccb3f4475; style ee5ad6db-d9d4-4ae4-9d69-c37ccb3f4475 stroke:#2c3143,stroke-width:4px; 14["Summary-Neoantigen"]; 13 -->|classified| 14; dbcedf04-dffe-49bc-bac5-a3ef2d41fabd["Output\nNeoantigen_summary"]; 14 --> dbcedf04-dffe-49bc-bac5-a3ef2d41fabd; style dbcedf04-dffe-49bc-bac5-a3ef2d41fabd stroke:#2c3143,stroke-width:4px;
Inputs
Input | Label |
---|---|
Input dataset | Novel_Peptides |
Input dataset | Fragpipe-Peptide-Report |
Input dataset | Annotated-GffCompared-GTFtoBED |
Input dataset | Homo_sapiens.GRCh38_canon.106.gtf |
Outputs
From | Output | Label |
---|---|---|
toolshed.g2.bx.psu.edu/repos/iuc/query_tabular/query_tabular/3.3.2 | Query Tabular | Peptide_to_Protein_Annotation |
toolshed.g2.bx.psu.edu/repos/devteam/tabular_to_fasta/tab2fasta/1.1.1 | Tabular-to-FASTA | FASTA-IEDB |
Convert characters1 | Convert | Converting_pipes_to_columns |
toolshed.g2.bx.psu.edu/repos/galaxyp/regex_find_replace/regexColumn1/1.0.3 | Column Regex Find And Replace | Modifying-string-name |
Convert characters1 | Convert | Converting_colons_to_columns |
toolshed.g2.bx.psu.edu/repos/iuc/query_tabular/query_tabular/3.3.2 | Query Tabular | Extracting-info-from-GFFtobed |
toolshed.g2.bx.psu.edu/repos/iuc/query_tabular/query_tabular/3.3.2 | Query Tabular | Table-processing-3 |
toolshed.g2.bx.psu.edu/repos/iuc/query_tabular/query_tabular/3.3.2 | Query Tabular | Peptide-location-generation |
toolshed.g2.bx.psu.edu/repos/iuc/query_tabular/query_tabular/3.3.2 | Query Tabular | BED-File-for-PepPointer |
toolshed.g2.bx.psu.edu/repos/galaxyp/pep_pointer/pep_pointer/0.1.3+galaxy1 | PepPointer | PepPointer |
toolshed.g2.bx.psu.edu/repos/iuc/query_tabular/query_tabular/3.3.2 | Query Tabular | Summary-Neoantigen |
Tools
To use these workflows in Galaxy you can either click the links to download the workflows, or you can right-click and copy the link to the workflow which can be used in the Galaxy form to import workflows.
Importing into Galaxy
Below are the instructions for importing these workflows directly into your Galaxy server of choice to start using them!Hands-on: Importing a workflow
- Click on Workflow on the top menu bar of Galaxy. You will see a list of all your workflows.
- Click on galaxy-upload Import at the top-right of the screen
- Provide your workflow
- Option 1: Paste the URL of the workflow into the box labelled “Archived Workflow URL”
- Option 2: Upload the workflow file in the box labelled “Archived Workflow File”
- Click the Import workflow button
Below is a short video demonstrating how to import a workflow from GitHub using this procedure:
Version History
Version | Commit | Time | Comments |
---|---|---|---|
1 | 6e4ce4916 | 2024-11-14 15:41:21 | Made sure the order is right |
For Admins
Installing the workflow tools
wget https://training.galaxyproject.org/training-material/topics/proteomics/tutorials/neoantigen-5-variant-annotation/workflows/main_workflow.ga -O workflow.ga workflow-to-tools -w workflow.ga -o tools.yaml shed-tools install -g GALAXY -a API_KEY -t tools.yaml workflow-install -g GALAXY -a API_KEY -w workflow.ga --publish-workflows