PyCaret - LORIS Tutorial

topics/statistics/tutorials/loris_model/README.md

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+# Tutorial_Galaxy-Pycaret
+A Galaxy tutorial to create and run a logistic regression classifier with LORIS dataset (Chang et al., 2024)

topics/statistics/tutorials/loris_model/data-library.yaml

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+---
+destination:
+  type: library
+  name: GTN - Material
+  description: Galaxy Training Network Material
+  synopsis: Galaxy Training Network Material. See https://training.galaxyproject.org
+items:
+- name: New topic
+  description: Topic summary
+  items:
+  - name: LORIS LLR6 model build
+    items:
+    - name: 'DOI: 10.5281/zenodo.13885908'
+      description: latest
+      items:
+      - url: https://zenodo.org/api/records/13885908/files/Chowell_train_Response.tsv/content
+        src: url
+        ext: ''
+        info: https://zenodo.org/records/13885908
+      - url: https://zenodo.org/api/records/13885908/files/Chowell_test_Response.tsv/content
+        src: url
+        ext: ''
+        info: https://zenodo.org/records/13885908

topics/statistics/tutorials/loris_model/faqs/index.md

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+---
+layout: faq-page
+---

topics/statistics/tutorials/loris_model/tutorial.bib

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+
+# This is the bibliography file for your tutorial.
+#
+# To add bibliography (bibtex) entries here, follow these steps:
+#  1) Find the DOI for the article you want to cite
+#  2) Go to https://doi2bib.org and fill in the DOI
+#  3) Copy the resulting bibtex entry into this file
+#
+# To cite the example below, in your tutorial.md file
+# use {% cite Batut2018 %}
+#
+# If you want to cite an online resourse (website etc)
+# you can use the 'online' format (see below)
+#
+# You can remove the examples below
+
+@article{Chang2024,
+  title = {LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical,  pathologic and genomic features},
+  volume = {5},
+  ISSN = {2662-1347},
+  url = {http://dx.doi.org/10.1038/s43018-024-00772-7},
+  DOI = {10.1038/s43018-024-00772-7},
+  number = {8},
+  journal = {Nature Cancer},
+  publisher = {Springer Science and Business Media LLC},
+  author = {Chang,  Tian-Gen and Cao,  Yingying and Sfreddo,  Hannah J. and Dhruba,  Saugato Rahman and Lee,  Se-Hoon and Valero,  Cristina and Yoo,  Seong-Keun and Chowell,  Diego and Morris,  Luc G. T. and Ruppin,  Eytan},
+  year = {2024},
+  month = jun,
+  pages = {1158–1175}
+}
+@online{gtn-website,
+  author = {GTN community},
+  title = {GTN Training Materials: Collection of tutorials developed and maintained by the worldwide Galaxy community},
+  url = {https://training.galaxyproject.org},
+  urldate = {2021-03-24}
+}

topics/statistics/tutorials/loris_model/workflows/index.md

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+---
+layout: workflow-list
+---

topics/statistics/tutorials/loris_model/workflows/main_workflow-tests.yml

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+- doc: Test the PyCaret comparison workflow
+  job:
+    'chowell_train':
+      location: https://zenodo.org/records/13885908/files/Chowell_train_Response.tsv
+      class: File
+      filetype: .tsv
+    'chowell_test':
+      location: https://zenodo.org/records/13885908/files/Chowell_test_Response.tsv
+      class: File
+      filetype: .tsv
+  outputs:
+    comparison_result:
+      asserts:
+        has_text:
+          text: "Model Training Report"
+    model:
+      asserts:
+        has_text:
+          text: "pycaret.internal.pipeline"

topics/statistics/tutorials/loris_model/workflows/main_workflow.ga

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+{
+    "a_galaxy_workflow": "true",
+    "annotation": "Generates LORIS LLR6 model ",
+    "creator":[
+      {
+         "class":"Person",
+         "identifier":"https://orcid.org/0000-0002-4403-6684",
+         "name":"Paulo Cilas Morais Lyra Junior"
+      },
+      {
+         "class":"Person",
+         "identifier":"https://orcid.org/0009-0005-4322-3401",
+         "name":"Junhao Qiu"
+      },
+      {
+         "class":"Person",
+         "identifier":"https://orcid.org/0000-0002-4583-5226",
+         "name":"Jeremy Goecks"
+      }
+   ],
+   "format-version":"0.1",
+   "license": "AGPL-3.0-or-later",
+   "name":"Ludwig - Image recognition model - MNIST",    
+   "steps": {
+        "0": {
+            "annotation": "Chowell train cohort - 964 samples",
+            "content_id": null,
+            "errors": null,
+            "id": 0,
+            "input_connections": {},
+            "inputs": [
+                {
+                    "description": "",
+                    "name": "Chowell_Train_Response.tsv"
+                }
+            ],
+            "label": "Chowell_Train_Response.tsv",
+            "name": "Input dataset",
+            "outputs": [],
+            "position": {
+                "bottom": 292.9513931274414,
+                "height": 82.46527862548828,
+                "left": 356.9618225097656,
+                "right": 556.9618377685547,
+                "top": 210.48611450195312,
+                "width": 200.00001525878906,
+                "x": 356.9618225097656,
+                "y": 210.48611450195312
+            },
+            "tool_id": null,
+            "tool_state": "{\"optional\": false, \"tag\": \"\"}",
+            "tool_version": null,
+            "type": "data_input",
+            "uuid": "53bffd14-f503-4c81-8eb2-e70c0cec0559",
+            "workflow_outputs": [
+                {
+                    "label": null,
+                    "output_name": "output",
+                    "uuid": "66a19810-a401-47b6-8983-98e3f5e8757e"
+                }
+            ]
+        },
+        "1": {
+            "annotation": "Chowell test cohort - 515 samples",
+            "content_id": null,
+            "errors": null,
+            "id": 1,
+            "input_connections": {},
+            "inputs": [
+                {
+                    "description": "",
+                    "name": "Chowell_Test_Response.tsv"
+                }
+            ],
+            "label": "Chowell_Test_Response.tsv",
+            "name": "Input dataset",
+            "outputs": [],
+            "position": {
+                "bottom": 402.9513931274414,
+                "height": 82.46527862548828,
+                "left": 355.97222900390625,
+                "right": 555.9722442626953,
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+                "width": 200.00001525878906,
+                "x": 355.97222900390625,
+                "y": 320.4861145019531
+            },
+            "tool_id": null,
+            "tool_state": "{\"optional\": false, \"tag\": \"\"}",
+            "tool_version": null,
+            "type": "data_input",
+            "uuid": "176d36e8-a459-4f51-9cff-932952f07f2f",
+            "workflow_outputs": [
+                {
+                    "label": null,
+                    "output_name": "output",
+                    "uuid": "2b5382f7-f9b6-4715-aaf7-87e27fbdf8c6"
+                }
+            ]
+        },
+        "2": {
+            "annotation": "",
+            "content_id": "pycaret_tool",
+            "errors": null,
+            "id": 2,
+            "input_connections": {
+                "input_file": {
+                    "id": 0,
+                    "output_name": "output"
+                },
+                "test_file": {
+                    "id": 1,
+                    "output_name": "output"
+                }
+            },
+            "inputs": [
+                {
+                    "description": "runtime parameter for tool PyCaret Model Comparison",
+                    "name": "input_file"
+                },
+                {
+                    "description": "runtime parameter for tool PyCaret Model Comparison",
+                    "name": "test_file"
+                }
+            ],
+            "label": null,
+            "name": "PyCaret Model Comparison",
+            "outputs": [
+                {
+                    "name": "model",
+                    "type": "data"
+                },
+                {
+                    "name": "comparison_result",
+                    "type": "html"
+                }
+            ],
+            "position": {
+                "bottom": 507.48268127441406,
+                "height": 297.013916015625,
+                "left": 684.96533203125,
+                "right": 884.9653472900391,
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+                "width": 200.00001525878906,
+                "x": 684.96533203125,
+                "y": 210.46876525878906
+            },
+            "post_job_actions": {},
+            "tool_id": "pycaret_tool",
+            "tool_state": "{\"advanced_settings\": {\"customize_defaults\": \"false\", \"__current_case__\": 1}, \"input_file\": {\"__class__\": \"RuntimeValue\"}, \"model_selection\": {\"model_type\": \"regression\", \"__current_case__\": 1, \"regression_models\": null}, \"random_seed\": \"42\", \"target_feature\": \"\", \"test_file\": {\"__class__\": \"RuntimeValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+            "tool_version": "3.3.2+0",
+            "type": "tool",
+            "uuid": "2a5e0015-457e-475f-97aa-72183a56af18",
+            "workflow_outputs": [
+                {
+                    "label": "PyCaret Model Comparison best model on input dataset(s)",
+                    "output_name": "model",
+                    "uuid": "5925cd98-b856-4dc2-87ae-0b07f2844386"
+                },
+                {
+                    "label": "PyCaret Model Comparison Comparison result on input dataset(s)",
+                    "output_name": "comparison_result",
+                    "uuid": "a292d802-b28f-4707-862c-5454e4ebb886"
+                }
+            ]
+        }
+    },
+    "tags":[
+	"LORIS",
+	"LLR6_model",
+	"Chowell_train_test",
+	"Logistic_Regression_Model"
+    ],
+    "uuid":"a59d72a3-a167-4f94-87ea-0e3e18df1d4c",
+    "version": 1
+}