GTN_Exemplar_002_TMA_workflow_Feb2025

imaging-multiplex-tissue-imaging-TMA/gtn-exemplar-002-tma-workflow-feb2025

Author(s)
Cameron Watson
Version
1
Last updated
Mar 13, 2025
License
MIT
Tags
imaging

Features
Tutorial
End-to-End Tissue Microarray Image Analysis with Galaxy-ME
Workflow Testing
Tests: ✅
Results: Not yet automated
FAIRness PURL
https://gxy.io/GTN:W00318
RO-Crate logo with flask Download Workflow RO-Crate
Launch in Tutorial Mode
Download 
flowchart TD
  0["ℹ️ Input Dataset\nmarkers.csv"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nPhenotypeWorkflow"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Collection\nRaw cycle images"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["Illumination correction with Basic"];
  2 -->|output| 3;
  8a05fb69-9e2b-4fa4-ab8c-77d3241f7a86["Output\nDFP images"];
  3 --> 8a05fb69-9e2b-4fa4-ab8c-77d3241f7a86;
  style 8a05fb69-9e2b-4fa4-ab8c-77d3241f7a86 stroke:#2c3143,stroke-width:4px;
  a5432ed5-980f-4f04-83a2-b5514019b11b["Output\nFFP images"];
  3 --> a5432ed5-980f-4f04-83a2-b5514019b11b;
  style a5432ed5-980f-4f04-83a2-b5514019b11b stroke:#2c3143,stroke-width:4px;
  4["Stitching and registration with Ashlar"];
  3 -->|output_dfp| 4;
  3 -->|output_ffp| 4;
  2 -->|output| 4;
  0 -->|output| 4;
  81f2c552-cd84-4d48-af14-eb252550f35a["Output\nRegistered image"];
  4 --> 81f2c552-cd84-4d48-af14-eb252550f35a;
  style 81f2c552-cd84-4d48-af14-eb252550f35a stroke:#2c3143,stroke-width:4px;
  5["TMA dearray with UNetCoreograph"];
  4 -->|output| 5;
  d79b4449-f879-42a9-9c79-0e0a6df0fa79["Output\nDearray images"];
  5 --> d79b4449-f879-42a9-9c79-0e0a6df0fa79;
  style d79b4449-f879-42a9-9c79-0e0a6df0fa79 stroke:#2c3143,stroke-width:4px;
  c3ae2005-725a-487c-a77a-437636f3a296["Output\nTMA dearray map"];
  5 --> c3ae2005-725a-487c-a77a-437636f3a296;
  style c3ae2005-725a-487c-a77a-437636f3a296 stroke:#2c3143,stroke-width:4px;
  0ed3e920-42ce-457d-9ebe-f0cd0baa1dea["Output\nDearray masks"];
  5 --> 0ed3e920-42ce-457d-9ebe-f0cd0baa1dea;
  style 0ed3e920-42ce-457d-9ebe-f0cd0baa1dea stroke:#2c3143,stroke-width:4px;
  6["Nuclear segmentation"];
  5 -->|tma_sections| 6;
  65c32086-b193-440f-b1a1-e5731bda0820["Output\nNuclear mask"];
  6 --> 65c32086-b193-440f-b1a1-e5731bda0820;
  style 65c32086-b193-440f-b1a1-e5731bda0820 stroke:#2c3143,stroke-width:4px;
  7["Convert dearray images to OME-TIFF"];
  5 -->|tma_sections| 7;
  d1c85ec4-1aea-48ce-88c3-ede346d9b34f["Output\nConverted image"];
  7 --> d1c85ec4-1aea-48ce-88c3-ede346d9b34f;
  style d1c85ec4-1aea-48ce-88c3-ede346d9b34f stroke:#2c3143,stroke-width:4px;
  8["Cell feature quantification with MC-Quant"];
  0 -->|output| 8;
  5 -->|tma_sections| 8;
  6 -->|mask| 8;
  a277be13-b5af-4591-b86b-a8679f561677["Output\nPrimary Mask Quantification"];
  8 --> a277be13-b5af-4591-b86b-a8679f561677;
  style a277be13-b5af-4591-b86b-a8679f561677 stroke:#2c3143,stroke-width:4px;
  9["Rename OME-TIFF channels"];
  0 -->|output| 9;
  7 -->|output| 9;
  0867cba2-0ac1-413d-b6d0-aba8b2dcbe0c["Output\nRenamed image"];
  9 --> 0867cba2-0ac1-413d-b6d0-aba8b2dcbe0c;
  style 0867cba2-0ac1-413d-b6d0-aba8b2dcbe0c stroke:#2c3143,stroke-width:4px;
  10["Convert to Anndata"];
  8 -->|cellmask| 10;
  a10efe57-5e36-4625-8ac8-a4bd27b3ce7e["Output\nAnndata feature table"];
  10 --> a10efe57-5e36-4625-8ac8-a4bd27b3ce7e;
  style a10efe57-5e36-4625-8ac8-a4bd27b3ce7e stroke:#2c3143,stroke-width:4px;
  11["Scimap phenotyping"];
  10 -->|outfile| 11;
  1 -->|output| 11;
  1711b39d-79db-4012-80b6-abfae28439ae["Output\nPhenotyped feature table"];
  11 --> 1711b39d-79db-4012-80b6-abfae28439ae;
  style 1711b39d-79db-4012-80b6-abfae28439ae stroke:#2c3143,stroke-width:4px;
  12["Create a Vitessce dashboard"];
  11 -->|output| 12;
  9 -->|renamed_image| 12;
  6 -->|mask| 12;
  9093603f-8ee1-424b-8520-c5f5d3e9dc3d["Output\nVitessce dashboard"];
  12 --> 9093603f-8ee1-424b-8520-c5f5d3e9dc3d;
  style 9093603f-8ee1-424b-8520-c5f5d3e9dc3d stroke:#2c3143,stroke-width:4px;

Inputs

Input Label
Input dataset markers.csv
Input dataset PhenotypeWorkflow
Input dataset collection Raw cycle images

Outputs

From Output Label
toolshed.g2.bx.psu.edu/repos/perssond/basic_illumination/basic_illumination/1.1.1+galaxy2 BaSiC Illumination Illumination correction with Basic
toolshed.g2.bx.psu.edu/repos/perssond/ashlar/ashlar/1.18.0+galaxy1 ASHLAR Stitching and registration with Ashlar
toolshed.g2.bx.psu.edu/repos/perssond/coreograph/unet_coreograph/2.2.8+galaxy1 UNetCoreograph TMA dearray with UNetCoreograph
toolshed.g2.bx.psu.edu/repos/goeckslab/mesmer/mesmer/0.12.3+galaxy3 Perform segmentation of multiplexed tissue data Nuclear segmentation
toolshed.g2.bx.psu.edu/repos/imgteam/bfconvert/ip_convertimage/6.7.0+galaxy0 Convert image Convert dearray images to OME-TIFF
toolshed.g2.bx.psu.edu/repos/perssond/quantification/quantification/1.6.0+galaxy0 MCQUANT Cell feature quantification with MC-Quant
toolshed.g2.bx.psu.edu/repos/goeckslab/rename_tiff_channels/rename_tiff_channels/0.0.2+galaxy1 Rename OME-TIFF channels Rename OME-TIFF channels
toolshed.g2.bx.psu.edu/repos/goeckslab/scimap_mcmicro_to_anndata/scimap_mcmicro_to_anndata/2.1.0+galaxy2 Convert McMicro Output to Anndata Convert to Anndata
toolshed.g2.bx.psu.edu/repos/goeckslab/scimap_phenotyping/scimap_phenotyping/2.1.0+galaxy2 Single Cell Phenotyping Scimap phenotyping
toolshed.g2.bx.psu.edu/repos/goeckslab/vitessce_spatial/vitessce_spatial/3.5.1+galaxy0 Vitessce Create a Vitessce dashboard

Tools

Tool Links
toolshed.g2.bx.psu.edu/repos/goeckslab/mesmer/mesmer/0.12.3+galaxy3 View in ToolShed
toolshed.g2.bx.psu.edu/repos/goeckslab/rename_tiff_channels/rename_tiff_channels/0.0.2+galaxy1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/goeckslab/scimap_mcmicro_to_anndata/scimap_mcmicro_to_anndata/2.1.0+galaxy2 View in ToolShed
toolshed.g2.bx.psu.edu/repos/goeckslab/scimap_phenotyping/scimap_phenotyping/2.1.0+galaxy2 View in ToolShed
toolshed.g2.bx.psu.edu/repos/goeckslab/vitessce_spatial/vitessce_spatial/3.5.1+galaxy0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/imgteam/bfconvert/ip_convertimage/6.7.0+galaxy0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/perssond/ashlar/ashlar/1.18.0+galaxy1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/perssond/basic_illumination/basic_illumination/1.1.1+galaxy2 View in ToolShed
toolshed.g2.bx.psu.edu/repos/perssond/coreograph/unet_coreograph/2.2.8+galaxy1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/perssond/quantification/quantification/1.6.0+galaxy0 View in ToolShed

To use these workflows in Galaxy you can either click the links to download the workflows, or you can right-click and copy the link to the workflow which can be used in the Galaxy form to import workflows.

Importing into Galaxy

Below are the instructions for importing these workflows directly into your Galaxy server of choice to start using them!
Hands On: Importing a workflow
  1. Click on Workflows in the Galaxy activity bar (on the left side of the screen, or in the top menu bar of older Galaxy instances). You will see a list of all your workflows
  2. Click on Import at the top-right of the screen
  3. Provide your workflow
    • Option 1: Paste the URL of the workflow into the box labelled “Archived Workflow URL”
    • Option 2: Upload the workflow file in the box labelled “Archived Workflow File”
  4. Click the Import workflow button

Below is a short video demonstrating how to import a workflow from GitHub using this procedure:

Video: Importing a workflow from URL

Version History

Version Commit Time Comments
4 5ec91efd3 2025-03-11 16:26:14 add redirect. Use smaller test data for CI. add workflow annotations
3 ca2c7b0af 2025-03-05 16:36:03 add workflow step annotations, labels. rename -tests.yml file for linter
2 dc3710c1a 2025-03-04 21:36:11 add orcid to workflow for linting
1 5fe1d4e05 2025-03-04 21:27:15 fix small workflow errors, update answer key history, add workflow tests

For Admins

Installing the workflow tools

wget https://training.galaxyproject.org/training-material/topics/imaging/tutorials/multiplex-tissue-imaging-TMA/workflows/GTN_Exemplar_002_TMA_workflow_Feb2025.ga -O workflow.ga
workflow-to-tools -w workflow.ga -o tools.yaml
shed-tools install -g GALAXY -a API_KEY -t tools.yaml
workflow-install -g GALAXY -a API_KEY -w workflow.ga --publish-workflows