Convert numerous workflow imports to automatic versions

topics/assembly/tutorials/largegenome/tutorial.md

@@ -184,11 +184,9 @@ Options:
 
 > <hands-on-title>Run the Data QC workflow</hands-on-title>
 >
-> 1. **Import the Data QC workflow** into Galaxy:
->    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/Galaxy-Workflow-Data_QC.ga) or download it to your computer.
->    - Import the workflow into Galaxy
+> 1. **Import the workflow** into Galaxy:
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/assembly/tutorials/largegenome/workflows/Galaxy-Workflow-Data_QC.ga" title="Galaxy Workflow Data QC" %}
 >
 >    - Click "Expand to full workflow form"
 >
@@ -270,7 +268,9 @@ Options:
 >    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/Galaxy-Workflow-kmer_counting.ga) or download it to your computer.
 >    - Import the workflow into Galaxy
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+> 1. **Import the workflow** into Galaxy:
+>
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/assembly/tutorials/largegenome/workflows/Galaxy-Workflow-kmer_counting.ga" title="Kmer counting workflow" %}
 >
 >    - Click "Expand to full workflow form"
 >
@@ -359,11 +359,9 @@ Options:
 
 > <hands-on-title>Run the Trim and Filter Reads workflow</hands-on-title>
 >
-> 1. **Import the Trim and Filter reads workflow** into Galaxy:
->    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/Galaxy-Workflow-Trim_and_filter_reads.ga) or download it to your computer.
->    - Import the workflow into Galaxy
+> 1. **Import the workflow** into Galaxy:
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/assembly/tutorials/largegenome/workflows/Galaxy-Workflow-Trim_and_filter_reads.ga" title="Trim and Filter reads" %}
 >
 >    - Click "Expand to full workflow form"
 >
@@ -459,11 +457,9 @@ Options
 
 > <hands-on-title>Run the Assembly with Flye workflow</hands-on-title>
 >
-> 1. **Import the Assembly with Flye workflow** into Galaxy:
->    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/Galaxy-Workflow-Assembly_with_Flye.ga) or download it to your computer.
->    - Import the workflow into Galaxy
+> 1. **Import the workflow** into Galaxy:
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/assembly/tutorials/largegenome/workflows/Galaxy-Workflow-Assembly_with_Flye.ga" title="Assembly with Flye" %}
 >
 >    - Click "Expand to full workflow form"
 >
@@ -572,11 +568,9 @@ Options:
 
 > <hands-on-title>Run the Assembly polishing workflow</hands-on-title>
 >
-> 1. **Import the Assembly polishing workflow** into Galaxy:
->    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/Galaxy-Workflow-Assembly_polishing.ga) or download it to your computer.
->    - Import the workflow into Galaxy
+> 1. **Import the workflow** into Galaxy:
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/assembly/tutorials/largegenome/workflows/Galaxy-Workflow-Assembly_polishing.ga" title="Assembly polishing workflow" %}
 >
 >    - Click "Expand to full workflow form"
 >
@@ -673,11 +667,9 @@ Options:
 
 > <hands-on-title>Run the Assess Genome Quality workflow</hands-on-title>
 >
-> 1. **Import the Assess Genome Quality workflow** into Galaxy:
->    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/Galaxy-Workflow-Assess_genome_quality.ga) or download it to your computer.
->    - Import the workflow into Galaxy
+> 1. **Import the workflow** into Galaxy:
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/assembly/tutorials/largegenome/workflows/Galaxy-Workflow-Assess_genome_quality.ga" title="Assess Genome Quality" %}
 >
 >    - Click "Expand to full workflow form"
 >

topics/computational-chemistry/tutorials/zauberkugel/tutorial.md

@@ -327,11 +327,7 @@ For pharmacophore-based protein target prediction, you can choose to use Galaxy
 >
 > Upload the Zauberkugel workflow from the following URL:
 >
-> ```
-> https://github.com/galaxyproject/training-material/blob/main/topics/computational-chemistry/tutorials/zauberkugel/workflows/main_workflow.ga
-> ```
->
-> {% snippet faqs/galaxy/workflows_import.md %}
+> {% snippet faqs/galaxy/workflows_run_trs.md path="topics/computational-chemistry/tutorials/zauberkugel/workflows/main_workflow.ga" title="Zauberkugel Workflow" %}
 >
 > The Zauberkugel workflow requires only two inputs; the ligand structure file (SMI format) and the ePharmaLib dataset (PHAR format). The output of the prediction of human targets of staurosporine performed with the ePharmaLib human target subset (<https://zenodo.org/record/6055897>) and this workflow is available as a [Galaxy history](https://usegalaxy.eu/u/aurelien_moumbock/h/zauberkugel).
 {: .hands_on}

topics/fair/tutorials/ro-crate-in-galaxy/tutorial.md

@@ -63,10 +63,8 @@ We will start by importing this workflow into your Galaxy account:
 > <hands-on-title>Import the workflow</hands-on-title>
 >
 > 1. **Import the workflow** into Galaxy
->    - Copy the URL (e.g. via right-click) of [this workflow](https://training.galaxyproject.org/training-material/topics/galaxy-interface/tutorials/workflow-reports/workflows/galaxy-101-everyone.ga) or download it to your computer.
->    - Import the workflow into Galaxy
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/galaxy-interface/tutorials/workflow-reports/workflows/galaxy-101-everyone.ga" title="Galaxy 101 for Everyone" %}
 >
 {: .hands_on}
 

topics/galaxy-interface/tutorials/workflow-reports/tutorial.md

@@ -63,10 +63,9 @@ We will start by importing this workflow into your Galaxy account:
 > <hands-on-title>Import the workflow</hands-on-title>
 >
 > 1. **Import the workflow** into Galaxy
->    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/galaxy-101-everyone.ga) or download it to your computer.
->    - Import the workflow into Galaxy
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="/topics/galaxy-interface/tutorials/workflow-reports/workflows/galaxy-101-everyone.ga" title="Galaxy 101 for Everyone" %}
+>
 >
 {: .hands_on}
 

topics/introduction/tutorials/galaxy-intro-101-everyone/tutorial.md

@@ -562,7 +562,7 @@ Galaxy makes this very easy with the `Extract workflow` option. This means any t
 > If you had problems extracting your workflow in the previous step, we provide [a working copy for you]({% link topics/introduction/tutorials/galaxy-intro-101-everyone/workflows/main_workflow.ga %}),
 > which you can import to Galaxy and use for the next sections (see below how to import a workflow to Galaxy).
 >
-> {% snippet faqs/galaxy/workflows_import.md %}
+> {% snippet faqs/galaxy/workflows_run_trs.md path="topics/introduction/tutorials/galaxy-intro-101-everyone/workflows/main_workflow.ga" title="Main Workflow" %}
 >
 {: .comment}
 

topics/proteomics/tutorials/metaproteomics/tutorial.md

@@ -93,11 +93,9 @@ We have a choice to run all these steps using a single workflow, then discuss ea
 
 > <hands-on-title>Pretreatments</hands-on-title>
 >
-> 1. **Import the workflow** into Galaxy
->    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/workflow.ga) or download it to your computer.
->    - Import the workflow into Galaxy
+> 1. **Import the workflow** into Galaxy:
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/proteomics/tutorials/metaproteomics/workflows/workflow.ga" title="Pretreatments" %}
 >
 > 2. Run **Workflow** {% icon workflow %} using the following parameters:
 >    - *"Send results to a new history"*: `No`

topics/proteomics/tutorials/metaquantome-data-creation/tutorial.md

@@ -117,11 +117,10 @@ We have a choice to run all these steps using a single workflow, then discuss ea
 
 > <hands-on-title>Pretreatments</hands-on-title>
 >
-> 1. **Import the workflow** into Galaxy
->    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/main_workflow.ga) or download it to your computer.
->    - Import the workflow into Galaxy
+> 1. **Import the workflow** into Galaxy:
+>
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/proteomics/tutorials/metaquantome-data-creation/workflows/main_workflow.ga" title="Pretreatments" %}
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
 >
 > 2. Run **Workflow** {% icon workflow %} using the following parameters:
 >    - *"Send results to a new history"*: `No`

topics/synthetic-biology/tutorials/basic_assembly_analysis/tutorial.md

@@ -199,9 +199,9 @@ In this section, you can run the Genetic Design - BASIC Assembly Workflow more e
 
 > <hands-on-title>Execute the entire workflow in one go.</hands-on-title>
 >
-> 1. Import your **Genetic Design - Basic Assembly Workflow** by uploading the [**workflow file**](https://training.galaxyproject.org/training-material/topics/synthetic-biology/tutorials/basic_assembly_analysis/workflows/Genetic_Design_BASIC_Assembly.ga).
+> 1. Import the workflow into Galaxy
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/synthetic-biology/tutorials/basic_assembly_analysis/workflows/Genetic_Design_BASIC_Assembly.ga" title="Genetic Design - Basic Assembly Workflow" %}
 >
 > 2. Click on *Workflow* on the top menu bar of Galaxy. You will see **Genetic Design - Basic Assembly Workflow**
 > 3. Click on the {% icon workflow-run %} (*Run workflow*) button next to your workflow

topics/synthetic-biology/tutorials/pathway_analysis/tutorial.md

@@ -245,9 +245,9 @@ In this section, you can run the Pathway Analysis Workflow more easily and fastl
 
 > <hands-on-title>Execute the entire workflow in one go.</hands-on-title>
 >
-> 1. Import your **Pathway Analysis Workflow** by uploading the [**workflow file**](https://training.galaxyproject.org/training-material/topics/synthetic-biology/tutorials/pathway_analysis/workflows/main_workflow.ga).
+> 1. Import the workflow into Galaxy
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/synthetic-biology/tutorials/pathway_analysis/workflows/main_workflow.ga" title="Pathway Analysis Workflow" %}
 >
 > 2. Click on *Workflow* on the top menu bar of Galaxy. You will see **Pathway Analysis Workflow**
 > 3. Click on the {% icon workflow-run %} (*Run workflow*) button next to your workflow
@@ -268,4 +268,4 @@ In this section, you can run the Pathway Analysis Workflow more easily and fastl
 
 To select the best pathways for producing the lycopene in *E. coli*, some metrics have to be estimated, namely production flux of the target and pathway thermodynamics. A global score is then computed by combining these criteria with others (pathway length, enzyme availability score, reaction SMARTS) using a machine learning model. These steps achieved using the tools of the presented Pathway Analysis workflow.
 
-![This scheme represents the pathway analysis workflow enabling the identification of the best pathways for producing a molecule of interest. To do that the workflow takes as input the collection of pathways to be scored and the metabolic model of the chassis (all files are SBMLs). Iteratively, each pathway is merged with the chassis model, and several metrics are evaluated such as the target production flux (using the rpFBA tool) and the thermodynamics of the pathway (using the rpThermo tool). A global score of each pathway combining these metrics with others is computed using a machine learning method (with the rpScore tool). Finally, the pathways are ranked from best to worst according to their global score (using the rpRanker tool). During the workflow, all metrics are stored as SBML annotations. The final output is a CSV file which contains the pathway IDs and their corresponding global score.](../../images/pathway_analysis_scheme.png)
+![This scheme represents the pathway analysis workflow enabling the identification of the best pathways for producing a molecule of interest. To do that the workflow takes as input the collection of pathways to be scored and the metabolic model of the chassis (all files are SBMLs). Iteratively, each pathway is merged with the chassis model, and several metrics are evaluated such as the target production flux (using the rpFBA tool) and the thermodynamics of the pathway (using the rpThermo tool). A global score of each pathway combining these metrics with others is computed using a machine learning method (with the rpScore tool). Finally, the pathways are ranked from best to worst according to their global score (using the rpRanker tool). During the workflow, all metrics are stored as SBML annotations. The final output is a CSV file which contains the pathway IDs and their corresponding global score.](../../images/pathway_analysis_scheme.png)

topics/synthetic-biology/tutorials/retrosynthesis_analysis/tutorial.md

@@ -257,9 +257,9 @@ In this section, you can run the RetroSynthesis Workflow more easily and fastly
 
 > <hands-on-title>Execute the entire workflow in one go.</hands-on-title>
 >
-> 1. Import your **RetroSynthesis workflow** by uploading the [**workflow file**](https://training.galaxyproject.org/training-material/topics/synthetic-biology/tutorials/basic_assembly_analysis/workflows/RetroSynthesis.ga).
+> 1. Import the workflow into Galaxy
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/synthetic-biology/tutorials/basic_assembly_analysis/workflows/RetroSynthesis.ga" title="RetroSynthesis workflow" %}
 >
 > 2. Click on *Workflow* on the top menu bar of Galaxy. You will see **RetroSynthesis** workflow.
 > 3. Click on the {% icon workflow-run %} (*Run workflow*) button next to your workflow

topics/transcriptomics/tutorials/rna-seq-reads-to-counts/tutorial.md

@@ -486,7 +486,7 @@ We'll use a prepared workflow to run the first few of the QCs below. This will a
 >    - Copy the URL (e.g. via right-click) of [this workflow]({{ site.baseurl }}{{ page.dir }}workflows/qc_report.ga) or download it to your computer.
 >    - Import the workflow into Galaxy
 >
->    {% snippet faqs/galaxy/workflows_import.md %}
+>    {% snippet faqs/galaxy/workflows_run_trs.md path="topics/transcriptomics/tutorials/rna-seq-reads-to-counts/workflows/qc_report.ga" title="QC Report" %}
 >
 > 2. Import this file as type BED file:
 >    ```