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Updates imaging tutorials to up-to-date tool names and parameters #4512

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Nov 14, 2023
Merged

Updates imaging tutorials to up-to-date tool names and parameters #4512

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7279e86
updates "Convert image format" tool
kostrykin Nov 13, 2023
277f46e
updates remaining tools of `imaging-introduction`
kostrykin Nov 13, 2023
f447a56
updates tools used in `hela-screen-analysis`
kostrykin Nov 13, 2023
79e04a5
updates renamed parameters
kostrykin Nov 14, 2023
822896b
fixes syntax for input/collapse pseudo-tools
kostrykin Nov 14, 2023
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50 changes: 25 additions & 25 deletions topics/imaging/tutorials/hela-screen-analysis/tutorial.md
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Expand Up @@ -19,7 +19,7 @@ objectives:
- "How to analyse extracted features from an imaging screen in Galaxy."
key_points:
- Galaxy workflows can be used to scale image analysis pipelines to whole screens.
- Segmented objects can be filtered using the **Filter segmentation** tool.
- Segmented objects can be filtered using the **Filter label map by rules** tool.
- Galaxy charts can be used to compare features extracted from screens showing cells with different treatments.
requirements:
-
Expand Down Expand Up @@ -79,7 +79,7 @@ The dataset required for this tutorial contains a screen of DAPI stained HeLa nu
>
> {% snippet faqs/galaxy/datasets_import_from_data_library.md %}
>
> 3. **Unzip file** {% icon tool %} with the following parameters:
> 3. {% tool [Unzip](toolshed.g2.bx.psu.edu/repos/imgteam/unzip/unzip/6.0+galaxy0) %} with the following parameters:
> - {% icon param-file %} *"input_file"*: `Zipped ` input file
> - *"Extract single file"*: `Single file`
> - *"Filepath"*: `B2--W00026--P00001--Z00000--T00000--dapi.tif`
Expand All @@ -88,7 +88,7 @@ The dataset required for this tutorial contains a screen of DAPI stained HeLa nu
>
> {% snippet faqs/galaxy/datasets_rename.md %}
>
> 5. **Unzip file** {% icon tool %} with the following parameters:
> 5. {% tool [Unzip](toolshed.g2.bx.psu.edu/repos/imgteam/unzip/unzip/6.0+galaxy0) %} with the following parameters:
> - {% icon param-file %} *"input_file"*: `Zipped ` input file
> - *"Extract single file"*: `All files`
>
Expand All @@ -106,7 +106,7 @@ The dataset required for this tutorial contains a screen of DAPI stained HeLa nu
>
> {% snippet faqs/galaxy/datasets_import_from_data_library.md %}
>
> 8. **Unzip** {% icon tool %} to extract the zipped screen:
> 8. {% tool [Unzip](toolshed.g2.bx.psu.edu/repos/imgteam/unzip/unzip/6.0+galaxy0) %} to extract the zipped screen:
> - {% icon param-file %} *"input_file"*: `Zipped ` input file
> - *"Extract single file"*: `All files`
>
Expand All @@ -131,32 +131,32 @@ First, we will create and test a workflow which extracts mean DAPI intensity, ar

> <hands-on-title>Create feature extraction workflow</hands-on-title>
>
> 1. **Filter Image** {% icon tool %} with the following parameters to smooth the image:
> - *"Image type"*: `Gaussian Blur`
> 1. {% tool [Filter 2D image](toolshed.g2.bx.psu.edu/repos/imgteam/2d_simple_filter/ip_filter_standard/0.0.3-3) %} with the following parameters to smooth the image:
> - *"Filter type"*: `Gaussian Blur`
> - *"Radius/Sigma"*: `3`
> - {% icon param-file %} *"Source file"*: `testinput.tif` file
> 2. **Auto Threshold** {% icon tool %} with the following parameters to segment the image:
> - {% icon param-file %} *"Source file"*: output of **Filter image** {% icon tool %}
> 2. {% tool [Threshold image](toolshed.g2.bx.psu.edu/repos/imgteam/2d_auto_threshold/ip_threshold/0.0.5-2) %} with the following parameters to segment the image:
> - {% icon param-file %} *"Source file"*: output of {% tool [Filter 2D image](toolshed.g2.bx.psu.edu/repos/imgteam/2d_simple_filter/ip_filter_standard/0.0.3-3) %}
> - *"Threshold Algorithm"*: `Otsu`
> - *"Dark Background"*: `Yes`
> 3. **Split objects** {% icon tool %} with the following parameters to split touching objects:
> - {% icon param-file %} *"Source file"*: output of **Auto Threshold** {% icon tool %}
> 3. {% tool [Split binary image using watershed transformation](toolshed.g2.bx.psu.edu/repos/imgteam/2d_split_binaryimage_by_watershed/ip_2d_split_binaryimage_by_watershed/0.0.1-2) %} with the following parameters to split touching objects:
> - {% icon param-file %} *"Source file"*: output of {% tool [Threshold image](toolshed.g2.bx.psu.edu/repos/imgteam/2d_auto_threshold/ip_threshold/0.0.5-2) %}
> - *"Minimum distance between two objects."*: `20`
> 4. **2D Feature Extraction** {% icon tool %} with the following parameters to extract features from the segmented objects:
> - {% icon param-file %} *"Label file"*: output of **Split objects** {% icon tool %}
> 4. {% tool [Extract 2D features](toolshed.g2.bx.psu.edu/repos/imgteam/2d_feature_extraction/ip_2d_feature_extraction/0.1.1-2) %} with the following parameters to extract features from the segmented objects:
> - {% icon param-file %} *"Label file"*: output of {% tool [Split binary image using watershed transformation](toolshed.g2.bx.psu.edu/repos/imgteam/2d_split_binaryimage_by_watershed/ip_2d_split_binaryimage_by_watershed/0.0.1-2) %}
> - *"Use original image to compute additional features."*: `No original image`
> - *"Select features to compute"*: `Select features`
> - *"Available features"*:
> - {% icon param-check %} `Add label id of label image`
> - {% icon param-check %} `Area`
> - {% icon param-check %} `Eccentricity`
> - {% icon param-check %} `Major Axis Length`
> 5. **Filter segmentation** {% icon tool %} with the following parameters to filter the label map from 3. with the extracted features and a set of rules:
> - {% icon param-file %} *"Source file"*: output of **Split objects** {% icon tool %}
> - {% icon param-file %} *"Feature file"*: output of **2D Feature Extraction** {% icon tool %}
> 5. {% tool [Filter label map by rules](toolshed.g2.bx.psu.edu/repos/imgteam/2d_filter_segmentation_by_features/ip_2d_filter_segmentation_by_features/0.0.1) %} with the following parameters to filter the label map from 3. with the extracted features and a set of rules:
> - {% icon param-file %} *"Source file"*: output of {% tool [Split binary image using watershed transformation](toolshed.g2.bx.psu.edu/repos/imgteam/2d_split_binaryimage_by_watershed/ip_2d_split_binaryimage_by_watershed/0.0.1-2) %}
> - {% icon param-file %} *"Feature file"*: output of {% tool [Extract 2D features](toolshed.g2.bx.psu.edu/repos/imgteam/2d_feature_extraction/ip_2d_feature_extraction/0.1.1-2) %}
> - {% icon param-file %} *"Rules file"*: rules file
> 6. **2D Feature Extraction** {% icon tool %} with the following parameters to extract features the final readout from the segmented objects:
> - {% icon param-file %} *"Label file"*: output of **Filter segmentation** {% icon tool %}
> 6. {% tool [Extract 2D features](toolshed.g2.bx.psu.edu/repos/imgteam/2d_feature_extraction/ip_2d_feature_extraction/0.1.1-2) %} with the following parameters to extract features the final readout from the segmented objects:
> - {% icon param-file %} *"Label file"*: output of {% tool [Filter label map by rules](toolshed.g2.bx.psu.edu/repos/imgteam/2d_filter_segmentation_by_features/ip_2d_filter_segmentation_by_features/0.0.1) %}
> - *"Use original image to compute additional features."*: `Use original image`
> - {% icon param-file %} *"Original image file"*: `testinput.tif` file
> - *"Select features to compute"*: `Select features`
Expand All @@ -166,13 +166,13 @@ First, we will create and test a workflow which extracts mean DAPI intensity, ar
> - {% icon param-check %} `Major Axis Length`
> 7. Now we can extract the workflow for batch processing
> - Name it "feature_extraction".
> - Remember to exclude **Unzip** {% icon tool %} by unchecking the tool.
> - Remember to exclude {% tool [Unzip](toolshed.g2.bx.psu.edu/repos/imgteam/unzip/unzip/6.0+galaxy0) %} by unchecking the tool.
> - Don't treat `B2.zip` and `B3.zip` as inputs (the workflow is supposed to be applied to the images directly).
>
> {% snippet faqs/galaxy/workflows_extract_from_history.md %}
>
> 8. Edit the workflow you just created
> - Add the tool **Input dataset** {% icon tool %} and name it `input image`.
> - Add the tool {% tool Input dataset %} and name it `input image`.
> - Name the input for the rules file `filter rules`.
> - Mark the results of steps 5 and 6 as outputs (by clicking on the asterisk next to the output name).
>
Expand All @@ -191,12 +191,12 @@ Now we want to apply our extracted workflow to `original data` and merge the res
> 1. Create a new workflow in the workflow editor.
>
> {% snippet faqs/galaxy/workflows_create_new.md %}
> 2. Add a **Input dataset collection** node and name it `input images`
> 3. Add a **Input dataset** node and name it `rules`
> 2. Add a {% tool Input dataset collection %} node and name it `input images`
> 3. Add a {% tool Input dataset %} node and name it `rules`
> 4. Add the **feature_extraction** workflow as node.
> - {% icon param-file %} *"input image"*: `input images` output of **Input dataset collection** {% icon tool %}
> - {% icon param-file %} *"filter rules"*: `rules` output of **Input dataset** {% icon tool %}
> 5. Add a **Collapse Collection** {% icon tool %} node.
> - {% icon param-file %} *"input image"*: `input images` output of {% tool Input dataset collection %}
> - {% icon param-file %} *"filter rules"*: `rules` output of {% tool Input dataset %}
> 5. Add a {% tool Collapse Collection %} node.
> - {% icon param-file %} *"Collection of files to collapse into single dataset"*: output of **feature_extraction** workflow
> - *"Keep one header line"*: `Yes`
> - *"Append File name"*: `No`
Expand Down Expand Up @@ -225,7 +225,7 @@ Finally, we want to plot the results for better interpretation.

> <hands-on-title>Plot feature extraction results</hands-on-title>
>
> 1. Click on the `Visualize this data` {% icon galaxy-barchart %} icon of the **Collapse Collection** {% icon tool %} results.
> 1. Click on the `Visualize this data` {% icon galaxy-barchart %} icon of the {% tool Collapse Collection %} results.
> 2. Run `Box plot` with the following parameters:
> - *"Provide a title"*: `Screen features`
> - *"X-Axis label"*:
Expand Down
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