| File Name: | Learn ChIP-Seq & ScATAC-Seq Data Analysis Using Linux and R |
| Content Source: | https://www.udemy.com/course/learn-chip-seq-scatac-seq-data-analysis-using-linux-and-r |
| Genre / Category: | Other Tutorials |
| File Size : | 2.1 GB |
| Publisher: | Rafiq Ur Rehman |
| Updated and Published: | August 2, 2025 |
Are you ready to dive into the world of gene regulation and chromatin accessibility using cutting-edge bioinformatics tools? This course, “Master ChIP-Seq and ATAC-Seq Analysis Using Linux and R,” is your gateway to understanding and performing real-world epigenomics data analysis from scratch.
Designed for students, researchers, and professionals in bioinformatics, biotechnology, and genomics, this hands-on course will take you on a comprehensive journey through ChIP-Seq (Chromatin Immunoprecipitation Sequencing) and ATAC-Seq (Assay for Transposase-Accessible Chromatin using sequencing) data analysis using powerful open-source tools.
You’ll start by understanding the theoretical concepts behind ChIP-Seq and ATAC-Seq technologies, including how they’re used to investigate protein-DNA interactions and chromatin accessibility in cells. These insights are essential in fields like cancer research, developmental biology, immunology, and beyond.
What You’ll Learn:
- The complete bioinformatics pipeline for ChIP-Seq and ATAC-Seq
- Setting up a Linux environment (even on Windows) for analysis
- Running quality checks and trimming raw sequencing reads
- Aligning reads to a reference genome and handling alignment files
- Performing peak calling with MACS2
- Annotating peaks and discovering DNA motifs using HOMER
- Understanding how single-cell ATAC-Seq works
- Analyzing scATAC-Seq datasets in R using the Signac and Seurat packages
- Visualizing chromatin accessibility and comparing multiple samples
Hands-On Linux and R Training
No prior experience with Linux or R? No problem. This course includes a full section on Linux for bioinformatics, where you’ll learn to navigate the file system, run basic commands, and handle biological data on the command line.
When working with single-cell ATAC-Seq data, we’ll shift to R—a powerful language for statistical analysis and visualization. You’ll get comfortable using RStudio, installing relevant packages, and working with real datasets from publicly available repositories like 10X Genomics and ENCODE.
DOWNLOAD LINK: Learn ChIP-Seq & ScATAC-Seq Data Analysis Using Linux and R
LearnAnalysis_Using_Linux_and_R.part1.rar – 1000.0 MB
LearnAnalysis_Using_Linux_and_R.part2.rar – 1000.0 MB
LearnAnalysis_Using_Linux_and_R.part3.rar – 123.9 MB
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