Merge branch 'main' into patch-13

Author: subinamehta

CONTRIBUTORS.yaml

@@ -1173,7 +1173,7 @@ hrhotz:
     contact_for_training: true
     location:
       country: CH
-      lat: 47.575694 
+      lat: 47.575694
       lon: 7.578796
     affiliations:
       - elixir-europe
@@ -2512,6 +2512,13 @@ sbenateau:
     affiliations:
       - elixir-europe
 
+sbueker77:
+    name: Sarah Büker
+    joined: 2025-05
+    affiliations:
+      - dsc-bremen
+      - uni-bremen
+
 scorreard:
     name: Solenne Correard
     email: [email protected]
@@ -2614,6 +2621,10 @@ sitjart:
     affiliations:
       - elixir-europe
 
+skschum:
+    name: Simeon Schum
+    joined: 2025-02
+
 slegras:
     name: Stéphanie Legras
     joined: 2017-09

ORGANISATIONS.yaml

@@ -41,6 +41,18 @@ carpentries:
     joined: 2021-09
     ror: "0356fgm10"
 
+dsc-bremen:
+    name: Data Science Center
+    url: https://www.dsc-ub.de
+    joined: 2025-05
+    avatar: "/training-material/shared/images/logos/data-science-center-uni-bremen.png"
+
+uni-bremen:
+    name: University of Bremen
+    joined: 2025-05
+    url: https://www.uni-bremen.de/
+    avatar: "/training-material/shared/images/logos/uni-bremen.png"
+
 deNBI:
     name: de.NBI
     url: https://www.denbi.de/

_includes/event-table.html

@@ -15,7 +15,7 @@
   <td>
 
 	  <a class="eventtable-title" href="{% if event.external %}{{event.external}}{% else %}{{site.baseurl}}{{event.url}}{% endif %}{% if include.campaign %}?utm_source=gtn&utm_medium=event-table&utm_campaign={{ include.campaign }}{% endif %}">{{event.title}}{% if event.draft %} (draft, will be hidden) {% endif %}</a>
-   <div class="eventtable-description"> {{event.description}} </div>
+   <div class="eventtable-description"> {{event.description | markdownify }} </div>
   </td>
   <td> {% if event.location %}{{event.location | format_location_short }} {% endif %} </td>
   <td> {% for org in event.contributions.organisers %}

events/2025-05-20-simplifying-data-science-with-galaxy-a-beginners-workshop.md

@@ -0,0 +1,25 @@
+---
+layout: event-external
+google_form_id: 1747063386
+title: 'Simplifying Data Science with Galaxy: A Beginner''s Workshop'
+description: |
+  This workshop aims to introduce participants to the Galaxy Project as
+  a powerful, open-source platform for data science and FAIR data management. Attendees
+  will learn how to process, analyze, and share data in a reproducible and accessible
+  way – without requiring advanced programming skills.  By the end, participants will
+  have hands-on experience using Galaxy to streamline workflows and enhance research
+  transparency.  For further information and registration, see the [event page](https://www.dsc-ub.de/verant_detail.php?id=262)
+external: https://www.dsc-ub.de/verant_detail.php?id=262
+contributions:
+  organisers:
+    - sbueker77
+  funding:
+    - dsc-bremen
+    - uni-bremen
+location:
+  name: Data Science Center Bremen
+  city: Bremen
+  country: Germany
+date_start: 2025-05-20
+date_end: 2025-05-20
+---

events/2025-05-26-bioinformatics-made-easy-a-hands-on-galaxy-workshop-for-biologists.md

@@ -0,0 +1,23 @@
+---
+layout: event-external
+google_form_id: 1747063630
+title: 'Bioinformatics Made Easy: A Hands-On Galaxy Workshop for Biologists'
+description: |
+  This workshop is designed for biologists and life scientists who want
+  to analyse sequence data using the Galaxy – without needing programming expertise.
+  Participants will learn how to perform key bioinformatics tasks.  By the end, attendees
+  will be able to apply FAIR and reproducible bioinformatics workflows to their own
+  research.  For further information and registration, please visit the [event page](https://www.dsc-ub.de/verant_detail.php?id=263)
+external: https://www.dsc-ub.de/verant_detail.php?id=263
+contributions:
+  organisers:
+    - sbueker77
+  funding:
+    - dsc-bremen
+    - uni-bremen
+location:
+  name: Data Science Center Bremen
+  city: Bremen
+  country: Germany
+date_start: 2025-05-26
+---

events/tracks/gta2024-assembly.md

@@ -24,7 +24,7 @@ contributions:
 program:
   - section: "Introduction"
     description: |
-      In this section, we will introduce what is a genome assembly, how it works, and the metrics to evaluate the quality of an assembly.
+      In this section, we will introduce what a genome assembly is, how it works, and the metrics to evaluate the quality of an assembly. **Warning: The QC training uses large data. For a lighter, faster version, follow the video and only use the sponge data**
     tutorials:
       - type: custom
         name: "[Introduction To Genome Assembly](https://youtu.be/9WZe7VGtr-k)"

faqs/galaxy/datasets_change_datatype.md

@@ -14,6 +14,6 @@ examples:
 
 * Click on the {% icon galaxy-pencil %} **pencil icon** for the dataset to edit its attributes
 * In the central panel, click {% icon galaxy-chart-select-data %} **Datatypes** tab on the top
-* In the {% icon galaxy-chart-select-data %} **Assign Datatype**, select {% if include.datatype %}`{{ include.datatype }}`{% else %} your desired datatype {% endif %} from "*New type*" dropdown  
+* In the {% icon galaxy-chart-select-data %} **Assign Datatype**, select {% if include.datatype %}`{{ include.datatype }}`{% else %} your desired datatype {% endif %} from "*New Type*" dropdown  
   - Tip: you can start typing the datatype into the field to filter the dropdown menu
 * Click the **Save** button

faqs/galaxy/datasets_convert_datatype.md

@@ -15,4 +15,4 @@ examples:
 * Click on the {% icon galaxy-pencil %} pencil icon for the dataset to edit its attributes.
 * In the central panel, click {% icon galaxy-chart-select-data %} Datatypes tab on the top.
 * In the {% icon galaxy-gear %} Convert to Datatype section, select {% if include.conversion %}`{{ include.conversion }}`{% else %} your desired datatype {% endif %} from "Target datatype" dropdown.
-* Click the **Create dataset** button to start the conversion.
+* Click the **Create Dataset** button to start the conversion.

learning-pathways/ml-using-python.md

@@ -6,7 +6,6 @@ cover-image-alt: ELIXIR logo
 
 editorial_board:
 - bebatut
-draft: true
 
 title: Artificial Intelligence and Machine Learning in Life Sciences using Python
 description: |

learning-pathways/neoantigen.md

@@ -0,0 +1,67 @@
+layout: learning-pathway
+tags: [intermediate, immunopeptidomics, cancer, proteogenomics, label-free]
+type: use
+
+title: Prediction of potential neoantigens
+description: |
+  This learning path introduces a comprehensive immunopeptidogenomics 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.
+
+cover-image: shared/images/proteomics.png
+cover-image-alt: image of a 3D protein folding structure
+
+editorial_board:
+- subinamehta
+
+pathway:
+  - section: "Neoantigen 1: Fusion-Database Generation"
+    description: |
+      Learn how to generate a personalized fusion peptide database using RNA-seq data. This step sets the foundation for identifying tumor-specific fusion peptides in downstream analyses.
+    tutorials:
+      - name: neoantigen-1-fusion-db-generation
+        topic: proteomics
+
+  - section: "Neoantigen 2: Non-Reference Database Generation"
+    description: |
+      Construct a non-reference proteogenomic database incorporating somatic mutations, indels, and other genomic alterations from VCF data.
+    tutorials:
+      - name: neoantigen-2-non-reference-database-generation
+        topic: proteomics
+
+  - section: "Neoantigen 3: Database Merge and FragPipe Discovery"
+    description: |
+      Merge the fusion and non-reference databases, then use FragPipe for mass spectrometry-based discovery of putative neopeptides.
+    tutorials:
+      - name: neoantigen-3-fragpipe-discovery
+        topic: proteomics
+
+  - section: "Neoantigen 4: PepQuery2 Verification"
+    description: |
+      Perform targeted verification of neoantigen candidates using PepQuery2 for peptide-spectrum match validation.
+    tutorials:
+      - name: neoantigen-4-peptide-verification
+        topic: proteomics
+
+  - section: "Neoantigen 5: Variant Annotation"
+    description: |
+      Annotate validated neopeptides with their corresponding genomic variants and protein context.
+    tutorials:
+      - name: neoantigen-5-variant-annotation
+        topic: proteomics
+
+  - section: "Neoantigen 6: Predicting HLA Binding"
+    description: |
+      Predict MHC binding affinity of validated neopeptides using tools such as NetMHCpan or similar.
+    tutorials:
+      - name: neoantigen-6-predicting-hla-binding
+        topic: proteomics
+
+  - section: "Neoantigen 7: IEDB Binding of PepQuery Validated Neopeptides"
+    description: |
+      Assess immunogenic potential of neopeptides by checking their binding predictions against immune epitope databases such as IEDB.
+    tutorials:
+      - name: neoantigen-7-hla-binding-novel-peptides
+        topic: proteomics
+
+---
+
+New to immunopeptidogenomics or neoantigen prediction? Follow this learning path to discover how label-free mass spectrometry and proteogenomic integration can accelerate identification of clinically relevant neoantigens and help in personalized immunotherapy.