Merge pull request #2109 from shiltemann/update-abr

[Metagenomics] Nanopore tutorial updates
galaxyproject · Oct 31, 2020 · c1ebf05 · c1ebf05
2 parents 705908a + b5e6ba3
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diff --git a/_config.yml b/_config.yml
@@ -97,6 +97,7 @@ icon-tag:
   feedback: far fa-comments
   galaxy-barchart: fas fa-chart-bar
   galaxy-chart-select-data: fas fa-database
+  galaxy-clear: fas fa-times-circle
   galaxy-columns: fas fa-columns
   galaxy-cross: fas fa-times
   galaxy-dropdown: fas fa-caret-down

diff --git a/shared/images/history_search_datasets.png b/shared/images/history_search_datasets.png
diff --git a/snippets/history_search.md b/snippets/history_search.md
@@ -0,0 +1,13 @@
+>
+>    > ### {% icon tip %} Tip: Searching your history
+>    >
+>    > To make it easier to find datasets in large histories, you can filter your history by keywords as follows:
+>    >  1. **Click** on the *search datasets* box at the top of the history panel.
+>    >
+>    >     ![history search box]({{site.baseurl}}/shared/images/history_search_datasets.png)
+>    >
+>    >  2. **Type** a search term in this box
+>    >     - For example a tool name, or sample name
+>    >  3. To undo the filtering and show your full history again, press on the *clear search* button {% icon galaxy-clear %} next to the search box
+>    {: .tip}
+>
diff --git a/snippets/scratchbook.md b/snippets/scratchbook.md
@@ -0,0 +1,16 @@
+>
+>    > ### {% icon tip %} Tip: Using the Scratchbook to view multiple datasets at once
+>    > If you would like to view two or more datasets at once, you can use the **Scratchbook** feature in Galaxy:
+>    >  1. **Click** on the *Scratchbook* icon {% icon galaxy-scratchbook%} on the top menu bar.
+>    >     - You should see a little checkmark on the icon now
+>    >  2. **View** {% icon galaxy-eye %} a dataset by clicking on the eye icon {% icon galaxy-eye %} to view the output
+>    >     - You should see the output in a window overlayed over Galaxy
+>    >     - You can resize this window by dragging the bottom-right corner
+>    >  3. **Click** outside the file to exit the Scratchbook
+>    >  4. **View** {% icon galaxy-eye %} a second dataset from your history
+>    >     - You should now see a second window with the new dataset
+>    >     - This makes it easier to compare the two outputs
+>    >  5. Repeat this for as many files as you would like to compare
+>    >  6. You can turn off the **Scratchbook** {% icon galaxy-scratchbook %} by clicking on the icon again
+>    {: .tip}
+>
diff --git a/topics/metagenomics/tutorials/plasmid-metagenomics-nanopore/tutorial.md b/topics/metagenomics/tutorials/plasmid-metagenomics-nanopore/tutorial.md
@@ -128,10 +128,10 @@ report page.
 
 > ### {% icon hands_on %} Hands-on: Plotting scripts for long read sequencing data
 >
-> 1. **NanoPlot** {% icon tool %} with the following parameters
->   - *"Select multifile mode"*: `batch`
->   - *"Type of the file(s) to work on"*: `fasta`
->   - *"files"*: The `Plasmids` dataset collection you just created
+> 1. {% tool [Nanoplot](tool toolshed.g2.bx.psu.edu/repos/iuc/nanoplot/nanoplot/1.28.2+galaxy1) %} with the following parameters
+>   - {% icon param-select %} *"Select multifile mode"*: `batch`
+>   - {% icon param-select %} *"Type of the file(s) to work on"*: `fasta`
+>   - {% icon param-collection %} *"files"*: The `Plasmids` dataset collection you just created
 >
 >     {% include snippets/select_collection.md %}
 >
@@ -178,14 +178,14 @@ the Minimap2 publication ({% cite Li2018 %}).
 
 > ### {% icon hands_on %} Hands-on: Pairwise sequence alignment
 >
-> 1. **Map with minimap2** {% icon tool %} with the following parameters
->    - *"Will you select a reference genome from your history or use a built-in index?"*: `Use a genome from history and build index`
->    - *"Use the following data collection as the reference sequence"*: `Created dataset collection (Plasmids)`
->    - *"Single or Paired-end reads"*: `Single`
->    - *"Select fastq dataset"*: The `Plasmids` dataset collection
->    - *"Select analysis mode (sets default)"*: `Oxford Nanopore all-vs--all overlap mapping`
+> 1. {% tool [Map with minimap2](toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.17+galaxy2) %} with the following parameters
+>    - {% icon param-select %} *"Will you select a reference genome from your history or use a built-in index?"*: `Use a genome from history and build index`
+>      - {% icon param-collection %} *"Use the following data collection as the reference sequence"*: `Plasmids` dataset collection we just created
+>    - {% icon param-select %} *"Single or Paired-end reads"*: `Single`
+>      - {% icon param-collection %} *"Select fastq dataset"*: The `Plasmids` dataset collection
+>      - {% icon param-select%} *"Select a profile of preset options"*: `Oxford Nanopore all-vs--all overlap mapping`
 >    - In the section **Set advanced output options**:
->      - *"Select an output format"*: `paf`
+>      - {% icon param-select %} *"Select an output format"*: `paf`
 >
 >    {% include snippets/select_collection.md %}
 >
@@ -231,9 +231,9 @@ Thus the per-base error rate is similar to the raw input reads.
 
 > ### {% icon hands_on %} Hands-on: De novo assembly
 >
-> 1. **miniasm** {% icon tool %} with the following parameters
->   - *"Sequence Reads"*: The `Plasmids` dataset collection
->   - *"PAF file"*: `Output Minimap dataset collection` created by **Minimap2** {% icon tool %}
+> 1. {% tool [miniasm](toolshed.g2.bx.psu.edu/repos/iuc/miniasm/miniasm/0.3+galaxy0) %} with the following parameters
+>   - {% icon param-collection %} *"Sequence Reads"*: The `Plasmids` dataset collection
+>   - {% icon param-collection %} *"PAF file"*: `Output Minimap dataset collection` created by **Minimap2** {% icon tool %}
 >
 >    {% include snippets/select_collection.md %}
 >
@@ -256,33 +256,34 @@ Remapping is done with the original reads, using the Miniasm assembly as a refer
 
 > ### {% icon hands_on %} Hands-on: Pairwise sequence alignment
 >
-> 1. **GFA to Fasta** {% icon tool %} with the following parameters
->   - *"Input GFA file"*: the `Assembly Graph` (collection) created by **Miniasm** {% icon tool %}
->
-> 2. **Map with minimap2** {% icon tool %} with the following parameters
->    - *"Will you select a reference genome from your history or use a built-in index?"*: `Use a genome from history and build index`
->    - *"Use the following dataset as the reference sequence"*: `FASTA file` collection created by **GFA to Fasta** {% icon tool %}
->    - *"Single or Paired-end reads"*: `single`
->    - *"Select fastq dataset"*: The `Plasmids` collection
->    - *"Select analysis mode (sets default)"*: `PacBio/Oxford Nanopore read to reference mapping (-Hk19)`
->    - In the section **Set advanced output options**:
->       - *"Select an output format"*: `paf`
->
->
->     {% include snippets/select_collection.md %}
+> 1. {% tool [GFA to Fasta](toolshed.g2.bx.psu.edu/repos/iuc/gfa_to_fa/gfa_to_fa/0.1.1) %} with the following parameters
+>   - {% icon param-collection %} *"Input GFA file"*: the `Assembly Graph` (collection) created by **Miniasm** {% icon tool %}
 >
 >     > ### {% icon question %} Question
 >     >
->     > How many contigs do we have for the RB05 sample after the use of **Minimap2** {% icon tool %} and **Miniasm** {% icon tool %}?
+>     > How many contigs do we have for the RB05 sample after de novo assembly?
 >     > <br><br>
 >     > Hint: run **Nanoplot** {% icon tool %} on the output of **GFA to Fasta** {% icon tool %}
 >     >
 >     > > ### {% icon solution %} Solution
->     > > 22
+>     > > 25
 >     > >
 >     > > This can be determined by looking at the NanoStats output of NanoPlot.
 >     > {: .solution }
 >     {: .question}
+>
+> 2. {% tool [Map with minimap2](toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.17+galaxy2) %} with the following parameters
+>    - {% icon param-select %} *"Will you select a reference genome from your history or use a built-in index?"*: `Use a genome from history and build index`
+>      - {% icon param-collection %} *"Use the following dataset as the reference sequence"*: `FASTA file` output from **GFA to Fasta** {% icon tool %} (collection)
+>    - {% icon param-select %} *"Single or Paired-end reads"*: `single`
+>      - {% icon param-collection %} *"Select fastq dataset"*: The `Plasmids` collection
+>      - {% icon param-select %} *"Select a profile of preset options"*:: `PacBio/Oxford Nanopore read to reference mapping (-Hk19)`
+>    - In the section **Set advanced output options**:
+>       - {% icon param-select %} *"Select an output format"*: `paf`
+>
+>
+>     {% include snippets/select_collection.md %}
+>
 {: .hands_on}
 
 ## Ultrafast consensus module using Racon
@@ -296,10 +297,10 @@ It supports data produced by both Pacific Biosciences and Oxford Nanopore Techno
 
 > ### {% icon hands_on %} Hands-on: Consensus module
 >
-> 1. **Racon** {% icon tool %} with the following parameters
->   - *"Sequences"*: The `Plasmids` dataset collection
->   - *"Overlaps"*: the latest `PAF file` collection created by **Minimap2** {% icon tool %}
->   - *"Target sequences"*: the `FASTA file` collection created by **GFA to Fasta** {% icon tool %}
+> 1. {% tool [Racon](toolshed.g2.bx.psu.edu/repos/bgruening/racon/racon/1.4.13) %} with the following parameters
+>   - {% icon param-collection %} *"Sequences"*: The `Plasmids` dataset collection
+>   - {% icon param-collection %} *"Overlaps"*: the latest `PAF file` collection created by **Minimap2** {% icon tool %}
+>   - {% icon param-collection %} *"Target sequences"*: the `FASTA file` collection created by **GFA to Fasta** {% icon tool %}
 >
 {: .hands_on}
 
@@ -326,8 +327,8 @@ By visualizing these assembly graphs, Bandage allows users to better understand,
 
 > ### {% icon hands_on %} Hands-on: Visualising de novo assembly graphs
 >
-> 1. **Bandage image** {% icon tool %} with the following parameters
->   - *"Graphical Fragment Assembly"*: the `Assembly graph` collection created by **Miniasm** {% icon tool %}
+> 1. {% tool [Bandage image](toolshed.g2.bx.psu.edu/repos/iuc/bandage/bandage_image/0.8.1+galaxy2) %} with the following parameters
+>   - {% icon param-collection %} *"Graphical Fragment Assembly"*: the `Assembly graph` collection created by **Miniasm** {% icon tool %}
 >
 > 2. Explore {% icon galaxy-eye %} the output images
 >
@@ -372,23 +373,34 @@ Let's try it on our data!
 
 > ### {% icon hands_on %} Hands-on: Unicycler assembly
 >
-> 1. **Create assemblies with Unicycler** {% icon tool %} with the following parameters
->   - *"Paired or Single end data"*: `None`
->   - *"Select long reads. If there are no long reads, leave this empty"*: The `Plasmids` dataset collection
+> 1. {% tool [Create assemblies with Unicycler](toolshed.g2.bx.psu.edu/repos/iuc/unicycler/unicycler/0.4.8.0) %} with the following parameters
+>   - {% icon param-select %} *"Paired or Single end data"*: `None`
+>   - {% icon param-collection %} *"Select long reads. If there are no long reads, leave this empty"*: The `Plasmids` dataset collection
 >
-> 2. **Bandage image** {% icon tool %} with the following parameters
->   - *"Graphical Fragment Assembly"*: the `Final Assembly Graph` collection created by **Unicycler** {% icon tool %}
+> 2. {% tool [Bandage image](toolshed.g2.bx.psu.edu/repos/iuc/bandage/bandage_image/0.8.1+galaxy2) %} with the following parameters
+>   - {% icon param-collection %} *"Graphical Fragment Assembly"*: the `Final Assembly Graph` collection created by **Unicycler** {% icon tool %}
 >
 > 3. Examine {% icon galaxy-eye %} the output images again
 >
-> > ### {% icon question %} Question
-> >
-> > For which samples has the plasmid assembly improved?
-> >
-> > > ### {% icon solution %} Solution
-> > > Exploring the outputs for all the samples reveals that many now display circular assemblies, indicating the full plasmids sequence was resolved.
-> > {: .solution }
-> {: .question}
+> 4. Use the **Scratchbook** {% icon galaxy-scratchbook %} to compare the two assemblies for sample `RB01`
+>    - Compare the **Bandage** {% icon tool %} images for our two assemblies:
+>      1. The assembly we got from running **minimap2, miniasm, racon** {% icon tool%} (first time we ran bandage)
+>      2. The assembly obtained with **Unicycler** {% icon tool %}
+>    - Tip: Search your history for the term `bandage` to easily find the outputs from our two bandage runs
+>
+>    {% include snippets/scratchbook.md %}
+>    {% include snippets/history_search.md %}
+>
+> 5. Repeat this comparison for the other samples.
+>
+>    > ### {% icon question %} Question
+>    >
+>    > For which samples has the plasmid assembly improved?
+>    >
+>    > > ### {% icon solution %} Solution
+>    > > Exploring the outputs for all the samples reveals that many now display circular assemblies, indicating the full plasmids sequence was resolved.
+>    > {: .solution }
+>    {: .question}
 >
 {: .hands_on}
 
@@ -410,8 +422,8 @@ It relies on the neural network models trained on full genome and plasmid sequen
 
 > ### {% icon hands_on %} Hands-on: Prediction of plasmid sequences
 >
-> 1. **PlasFlow** {% icon tool %} with the following parameters
->   - *"Sequence Reads"*: the `Final Assembly` collection created by **Unicycler** {% icon tool %}
+> 1. {% tool [PlasFlow](toolshed.g2.bx.psu.edu/repos/iuc/plasflow/PlasFlow/1.0) %} with the following parameters
+>   - {% icon param-collection %} *"Sequence Reads"*: the `Final Assembly` collection created by **Unicycler** {% icon tool %}
 >
 > > ### {% icon question %} Question
 > >
@@ -456,8 +468,8 @@ and compiles a summary report of detected antimicrobial resistance genes.
 
 > ### {% icon hands_on %} Hands-on: Prediction of AMR genes
 >
-> 1. **staramr** {% icon tool %} with the following parameters
->   - *"genomes"*: the `Final Assembly` collection created by **Unicycler**
+> 1. {% tool [staramr](toolshed.g2.bx.psu.edu/repos/nml/staramr/staramr_search/0.7.1+galaxy2) %} with the following parameters
+>   - {% icon param-collection %} *"genomes"*: the `Final Assembly` collection created by **Unicycler** {% icon tool %}
 >
 > > ### {% icon question %} Question
 > >
@@ -518,4 +530,3 @@ You have worked your way through the following pipeline:
 
 ![Workflow representation of this tutorial](../../images/plasmid-metagenomics-nanopore/Workflow.png)
 
-