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‎_plugins/jekyll-jsonld.rb‎

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'@type': 'Organization',
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'http://purl.org/dc/terms/conformsTo': {
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# Bioschemas profile
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'@id': 'https://bioschemas.org/profiles/Organization/0.2-DRAFT-2019_07_19',
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'@type': 'Organization'
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'@id': 'https://bioschemas.org/profiles/Organization/0.3-DRAFT',
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'@type': 'CreativeWork'
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},
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id: 'https://training.galaxyproject.org',
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email: '[email protected]',
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name: 'Galaxy Training Network',
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description: 'An organization providing a collection of tutorials developed and maintained by the worldwide Galaxy community',
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legalName: 'Galaxy Training Network',
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alternateName: 'GTN',
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url: 'https://training.galaxyproject.org',

‎faqs/galaxy/datasets_import_via_link.md‎

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---
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* Copy the link location
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* Click {% icon galaxy-upload %} **Upload Data** at the top of the tool panel
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* Click {% icon galaxy-upload %} **Upload** at the top of the activity panel
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{% if include.reset_form %}
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* Click **Reset** button at the bottom of the form. If the button is greyed out -> skip to the next step.
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{% endif %}

‎faqs/galaxy/workflows_hide_intermediate_steps.md‎

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When a workflow is executed, the user is usually primarily interested in the final product and not in all intermediate steps.
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By default all the outputs of a workflow will be shown, but we can explicitly tell Galaxy which outputs to show and which to hide for a given workflow.
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This behaviour is controlled by the little checkbox in front of every output dataset:
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This behaviour is controlled by clicking on the eye icon on for all dataset that should be hidden:
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![Asterisk for `out_file1` in the `Select First` tool]({% link shared/images/workflow_editor_mark_output.png %})
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![Asterisk for `out_file1` in the `Cut` tool]({% link shared/images/workflow_editor_hide_output.png %})
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‎learning-pathways/neoantigen.md‎

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description: |
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This learning path introduces a comprehensive immunopeptidogenomics (iPepGen) workflow for neoantigen discovery using label-free mass spectrometry data. The modules guide you through fusion and variant database generation, peptide identification with FragPipe, peptide validation using PepQuery2, and immunogenicity assessment through HLA binding predictions and IEDB screening.
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cover-image: shared/images/proteomics.png
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cover-image-alt: image of a 3D protein folding structure
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cover-image: shared/images/neoantigen_lp.png
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cover-image-alt: image of neoantigen mutation
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editorial_board:
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- subinamehta
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- name: neoantigen-hla-binding-novel-peptides
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topic: proteomics
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---
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New to immunopeptidogenomics or neoantigen prediction? Follow this learning path to discover how label-free mass spectrometry and proteogenomic integration can accelerate the identification of clinically relevant neoantigens and help in personalized immunotherapy.
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# Are you feeling adventurous? ✨
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## One-Click Neoantigen Workflow
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This new [One-Click Neoantigen Workflow](https://usegalaxy.eu/u/galaxyp/w/ipepgen-one-click-workflow) brings together all key modules of the neoantigen discovery process into a single, streamlined analysis within Galaxy. Instead of launching each tutorial separately, users can now execute the entire end-to-end pipeline—from database creation to HLA binding prediction—with just one click —without ever leaving Galaxy.
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