PeptideML

proteomics-ml-modeling-of-anti-cancer-peptides/peptideml

Author(s)

Version
1
Last updated
Jan 22, 2021
License
None Specified, defaults to CC-BY-4.0
Tags
proteomics

Features
Tutorial
Machine Learning Modeling of Anticancer Peptides
Workflow Testing
Tests: ❌
Results: Not yet automated
FAIRness PURL
https://gxy.io/GTN:W00164
RO-Crate logo with flask Download Workflow RO-Crate Workflowhub cloud with gears logo View on (Dev) WorkflowHub
Launch in Tutorial Mode
Download 
flowchart TD
  0["ℹ️ Input Dataset\nACPs"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nnon-ACPs"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["PDAUG Sequence Property Based Descriptors"];
  0 -->|output| 2;
  3["PDAUG Sequence Property Based Descriptors"];
  1 -->|output| 3;
  4["PDAUG Add Class Label"];
  2 -->|output1| 4;
  5["PDAUG Add Class Label"];
  3 -->|output1| 5;
  6["PDAUG Merge Dataframes"];
  4 -->|OutFile1| 6;
  5 -->|OutFile1| 6;
  7["PDAUG ML Models"];
  6 -->|output1| 7;
  8["PDAUG ML Models"];
  6 -->|output1| 8;
  9["PDAUG ML Models"];
  6 -->|output1| 9;
  10["PDAUG ML Models"];
  6 -->|output1| 10;
  11["PDAUG ML Models"];
  6 -->|output1| 11;
  12["PDAUG ML Models"];
  6 -->|output1| 12;
  13["PDAUG Merge Dataframes"];
  7 -->|output1| 13;
  9 -->|output1| 13;
  8 -->|output1| 13;
  10 -->|output1| 13;
  11 -->|output1| 13;
  12 -->|output1| 13;
  14["PDAUG Basic Plots"];
  13 -->|output1| 14;

Inputs

Input Label
Input dataset ACPs
Input dataset non-ACPs

Outputs

From Output Label
Input dataset ACPs
Input dataset non-ACPs
toolshed.g2.bx.psu.edu/repos/jay/pdaug_sequence_property_based_descriptors/pdaug_sequence_property_based_descriptors/0.1.0 PDAUG Sequence Property Based Descriptors
toolshed.g2.bx.psu.edu/repos/jay/pdaug_addclasslabel/pdaug_addclasslabel/0.1.0 PDAUG Add Class Label
toolshed.g2.bx.psu.edu/repos/jay/pdaug_merge_dataframes/pdaug_merge_dataframes/0.1.0 PDAUG Merge Dataframes
toolshed.g2.bx.psu.edu/repos/jay/pdaug_ml_models/pdaug_ml_models/0.1.0 PDAUG ML Models
toolshed.g2.bx.psu.edu/repos/jay/pdaug_merge_dataframes/pdaug_merge_dataframes/0.1.0 PDAUG Merge Dataframes
toolshed.g2.bx.psu.edu/repos/jay/pdaug_basic_plots/pdaug_basic_plots/0.1.0 PDAUG Basic Plots

Tools

Tool Links
toolshed.g2.bx.psu.edu/repos/jay/pdaug_addclasslabel/pdaug_addclasslabel/0.1.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/jay/pdaug_basic_plots/pdaug_basic_plots/0.1.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/jay/pdaug_merge_dataframes/pdaug_merge_dataframes/0.1.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/jay/pdaug_ml_models/pdaug_ml_models/0.1.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/jay/pdaug_sequence_property_based_descriptors/pdaug_sequence_property_based_descriptors/0.1.0 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
  • Click on Workflow on the top menu bar of Galaxy. You will see a list of all your workflows.
  • Click on Import at the top-right of the screen
  • 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”
  • 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
1 c6cb67762 2021-01-22 18:29:07 Tutorials for PDAUG tool suite (#2150)

For Admins

Installing the workflow tools

wget https://training.galaxyproject.org/training-material/topics/proteomics/tutorials/ml-modeling-of-anti-cancer-peptides/workflows/PeptideML.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