Epigenetics data analysis with Galaxy
purlPURL: https://gxy.io/GTN:P00028Comment: What is a Learning Pathway?
We recommend you follow the tutorials in the order presented on this page. They have been selected to fit together and build up your knowledge step by step. If a lesson has both slides and a tutorial, we recommend you start with the slides, then proceed with the tutorial.
Familiarize yourself with the Galaxy user interface and its most important features, then move on to analysis of genomic interval and deep-sequencing data with tools and tool suites like MACS2, bedtools and deepTools.
Module 1: Introduction to Galaxy
Get a first look at the Galaxy platform for data analysis. We start with a short introduction (video slides & practical) to familiarize you with the Galaxy interface, then proceed with slightly longer, but still introductory tutorials that demonstrate the handling of genomic intervals data in Galaxy.
Time estimation: 4 hours 40 minutes
Learning Objectives
- Learn how to upload a file
- Learn how to use a tool
- Learn how to view results
- Learn how to view histories
- Learn how to extract and run a workflow
- Learn how to share a history
- Familiarize yourself with the basics of Galaxy
- Learn how to obtain data from external sources
- Learn how to run tools
- Learn how histories work
- Learn how to create a workflow
- Learn how to share your work
- Familiarize yourself with the basics of Galaxy
- Learn how to obtain data from external sources
- Learn how to run tools
- Learn how histories work
- Learn how to create a workflow
- Learn how to share your work
| Lesson | Slides | Hands-on | Recordings |
|---|---|---|---|
| A short introduction to Galaxy | |||
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Galaxy Basics for genomics
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From peaks to genes
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Module 2: Analysis of ChIP-Seq, CUT&RUN and ATAC-Seq data
Learn how to perform mapping, peak calling with MACS-2, read depth analysis and correlation with the deepTools suite, and results vizualization with IGV and other tools for various chromatin selection assays.
Time estimation: 9 hours
Learning Objectives
- Inspect the read quality
- Trim low quality bases
- Map reads on a reference genome
- Assess the quality of a ChIP-seq experiment
- Extract coverage files
- Call enriched regions or peaks
- Apply appropriate analysis and quality control steps for CUT&RUN
- Apply an enrichment analysis and a robust peak detection
- Find protein binding motifs
- Apply appropriate analysis and quality control steps for ATAC-Seq
- Generate a heatmap of transcription start site accessibility
- Visualise peaks for specific regions
| Lesson | Slides | Hands-on | Recordings |
|---|---|---|---|
| Formation of the Super-Structures on the Inactive X | |||
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CUT&RUN data analysis
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ATAC-Seq data analysis
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Module 3: Analysis of DNA modification
Learn how to detect DNA methylation through sequencing and to analyze its distribution across genome regions.
Time estimation: 3 hours
Learning Objectives
- Learn how to analyse methylation data
- Get a first intuition what are common pitfalls.
| Lesson | Slides | Hands-on | Recordings |
|---|---|---|---|
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Introduction to DNA Methylation data analysis
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DNA Methylation data analysis
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Editorial Board
This material is reviewed by our Editorial Board:
Wolfgang Maier
Pavankumar Videm