Infinium Human Methylation BeadChip

epigenetics-ewas-suite/infinium-human-methylation-beadchip

Author(s)
Katarzyna Kamieniecka, Khaled Jum'ah, poterlowicz-lab
version Version
4
last_modification Last updated
Oct 23, 2023
license License
AGPL-3.0-or-later
galaxy-tags Tags
epigenetics

Features

Tutorial
hands_on Infinium Human Methylation BeadChip

Workflow Testing
Tests: ✅
Results: Not yet automated
FAIRness purl PURL
https://gxy.io/GTN:W00067
RO-Crate logo with flask Download Workflow RO-Crate Workflowhub cloud with gears logo View on WorkflowHub
Launch in Tutorial Mode question
galaxy-download Download
flowchart TD
  0["ℹ️ Input Dataset\nR01C02_Red.idat"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nR02C02_Red.idat"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\nR05C02_Red.idat"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["ℹ️ Input Dataset\nR06C02_Red.idat"];
  style 3 stroke:#2c3143,stroke-width:4px;
  4["ℹ️ Input Dataset\nR01C02_Green.idat"];
  style 4 stroke:#2c3143,stroke-width:4px;
  5["ℹ️ Input Dataset\nR02C02_Green.idat"];
  style 5 stroke:#2c3143,stroke-width:4px;
  6["ℹ️ Input Dataset\nR05C02_Green.idat"];
  style 6 stroke:#2c3143,stroke-width:4px;
  7["ℹ️ Input Dataset\nR06C02_Green.idat"];
  style 7 stroke:#2c3143,stroke-width:4px;
  8["ℹ️ Input Dataset\nphenotype Table txt file"];
  style 8 stroke:#2c3143,stroke-width:4px;
  9["ℹ️ Input Dataset\nUCSC Main on Human"];
  style 9 stroke:#2c3143,stroke-width:4px;
  10["Infinium Human Methylation BeadChip"];
  4 -->|output| 10;
  5 -->|output| 10;
  6 -->|output| 10;
  7 -->|output| 10;
  0 -->|output| 10;
  1 -->|output| 10;
  2 -->|output| 10;
  3 -->|output| 10;
  8 -->|output| 10;
  9 -->|output| 10;
  2ac7dd5d-ed74-4d58-b1cb-be7dcca9154a["Output\nSNPInfo Table"];
  10 --> 2ac7dd5d-ed74-4d58-b1cb-be7dcca9154a;
  style 2ac7dd5d-ed74-4d58-b1cb-be7dcca9154a stroke:#2c3143,stroke-width:4px;
  d1732a98-1861-4612-bdaa-f68861c22f56["Output\nDifferentially Methylated Regions"];
  10 --> d1732a98-1861-4612-bdaa-f68861c22f56;
  style d1732a98-1861-4612-bdaa-f68861c22f56 stroke:#2c3143,stroke-width:4px;
  9aa8b4a9-611e-4a39-864f-400f17866a9e["Output\nDifferentially Methylated Positions"];
  10 --> 9aa8b4a9-611e-4a39-864f-400f17866a9e;
  style 9aa8b4a9-611e-4a39-864f-400f17866a9e stroke:#2c3143,stroke-width:4px;
  14ddb6f7-637e-4193-bfb5-80aeae4fab64["Output\nQuality Control Report"];
  10 --> 14ddb6f7-637e-4193-bfb5-80aeae4fab64;
  style 14ddb6f7-637e-4193-bfb5-80aeae4fab64 stroke:#2c3143,stroke-width:4px;
  c8c37ff8-716d-4c23-a84f-7cebcb4b6c9d["Output\nQuality Control Plot"];
  10 --> c8c37ff8-716d-4c23-a84f-7cebcb4b6c9d;
  style c8c37ff8-716d-4c23-a84f-7cebcb4b6c9d stroke:#2c3143,stroke-width:4px;
  11["ChIPpeakAnno annoPeaks"];
  10 -->|dmp| 11;
  bedf4346-da4d-4e1a-bf3c-a7d20f3ec3c5["Output\nTable of Annotated Peaks"];
  11 --> bedf4346-da4d-4e1a-bf3c-a7d20f3ec3c5;
  style bedf4346-da4d-4e1a-bf3c-a7d20f3ec3c5 stroke:#2c3143,stroke-width:4px;
  12["Cut"];
  11 -->|tab| 12;
  0b54dfe5-f84a-4288-b631-ae4dc2384a17["Output\nCut on Table of Annotated Peaks"];
  12 --> 0b54dfe5-f84a-4288-b631-ae4dc2384a17;
  style 0b54dfe5-f84a-4288-b631-ae4dc2384a17 stroke:#2c3143,stroke-width:4px;
  13["Remove beginning"];
  12 -->|out_file1| 13;
  8f65cf82-7427-4273-ba0b-a6673ee1ff2d["Output\nRemove beginning on the cut output"];
  13 --> 8f65cf82-7427-4273-ba0b-a6673ee1ff2d;
  style 8f65cf82-7427-4273-ba0b-a6673ee1ff2d stroke:#2c3143,stroke-width:4px;
  14["Cluster Profiler Bitr"];
  13 -->|out_file1| 14;
  7989f80a-3e79-4d2f-bbe4-e4d641eebd6a["Output\nTable of Translated Gene ID's"];
  14 --> 7989f80a-3e79-4d2f-bbe4-e4d641eebd6a;
  style 7989f80a-3e79-4d2f-bbe4-e4d641eebd6a stroke:#2c3143,stroke-width:4px;
  15["Cluster Profiler GO"];
  14 -->|translation| 15;
  ff6c7018-b821-4ade-9931-fa99aeb0a86c["Output\nGO Enrichment Analysis of a Gene Set"];
  15 --> ff6c7018-b821-4ade-9931-fa99aeb0a86c;
  style ff6c7018-b821-4ade-9931-fa99aeb0a86c stroke:#2c3143,stroke-width:4px;
  03b88399-095b-4bd5-9693-528c60338407["Output\nGO Enrichment Analysis Visualization"];
  15 --> 03b88399-095b-4bd5-9693-528c60338407;
  style 03b88399-095b-4bd5-9693-528c60338407 stroke:#2c3143,stroke-width:4px;

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 galaxy-upload 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
4 4f69ebe91 2023-10-23 09:30:30 fix workflow
3 8f19faced 2023-10-19 14:31:03 fix
2 568e22f20 2023-10-19 14:06:20 add license
1 451efca00 2023-10-19 13:49:25 remove pictures and add output tests

For Admins

Installing the workflow tools

wget https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/ewas-suite/workflows/Infinium-Human-Methylation-BeadChip.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