Age Prediction DNA Methylation

statistics-age-prediction-with-ml/age-prediction-dnam

Author(s)

Version
6
Last updated
Jan 23, 2020
License
None Specified, defaults to CC-BY-4.0
Tags
statistics

Features
Tutorial
Age prediction using machine learning
Other workflows associated with this material
Workflow Testing
Tests: ❌
Results: Not yet automated
FAIRness PURL
https://gxy.io/GTN:W00218
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["Pipeline Builder"];
  1["ℹ️ Input Dataset\ntrain_dataset"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\ntest_dataset"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["ℹ️ Input Dataset\ntest_labels_dataset"];
  style 3 stroke:#2c3143,stroke-width:4px;
  4["Hyperparameter Search"];
  0 -->|outfile_params| 4;
  0 -->|outfile| 4;
  1 -->|output| 4;
  1 -->|output| 4;
  5["Ensemble methods"];
  2 -->|output| 5;
  4 -->|outfile_object| 5;
  6["Plot actual vs predicted curves and residual plots"];
  5 -->|outfile_predict| 6;
  3 -->|output| 6;

Inputs

Input Label
Input dataset train_dataset
Input dataset test_dataset
Input dataset test_labels_dataset

Outputs

From Output Label
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_build_pipeline/sklearn_build_pipeline/1.0.8.1 Pipeline Builder
Input dataset train_dataset
Input dataset test_dataset
Input dataset test_labels_dataset
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_searchcv/sklearn_searchcv/1.0.8.1 Hyperparameter Search
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_ensemble/sklearn_ensemble/1.0.8.1 Ensemble methods
toolshed.g2.bx.psu.edu/repos/bgruening/plotly_regression_performance_plots/plotly_regression_performance_plots/0.1 Plot actual vs predicted curves and residual plots

Tools

Tool Links
toolshed.g2.bx.psu.edu/repos/bgruening/plotly_regression_performance_plots/plotly_regression_performance_plots/0.1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_build_pipeline/sklearn_build_pipeline/1.0.8.1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_ensemble/sklearn_ensemble/1.0.8.1 View in ToolShed
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_searchcv/sklearn_searchcv/1.0.8.1 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
8 667ff3de9 2020-01-22 10:59:29 annotation
7 f7f017f33 2020-01-15 12:40:00 dna and rna capitals
6 eb4d724e0 2020-01-15 10:41:35 Workflow renaming
5 cad9f0a86 2019-12-29 22:28:05 Merge branch 'master' into ml_tools
4 0c8165c36 2019-12-26 20:08:40 update workflow
3 faf6d298a 2019-12-12 13:02:33 unflatten workflows
2 9d78b6434 2019-06-15 16:38:19 Add workflows
1 17a20f8e6 2019-01-25 10:34:58 Fine-tuning formatting

For Admins

Installing the workflow tools

wget https://training.galaxyproject.org/training-material/topics/statistics/tutorials/age-prediction-with-ml/workflows/age-prediction-dnam.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