This repository contains folders with different types of ChIP-seq analysis for various epigenetic modifications. Below is an overview of the contents:
Folder: H3K4me3
The H3K4me3 folder focuses on the analysis of ChIP-seq data specifically for the H3K4me3 epigenetic modification. It includes the following components:
- Data Preprocessing: Scripts and pipelines for quality control, adapter trimming, and read alignment.
- Peak Calling: Tools and methods for identifying enriched regions using peak calling algorithms.
- Peak Annotation: Scripts to annotate identified peaks with gene annotations, functional categories, and other genomic features.
- Differential Binding Analysis: Methods for comparing ChIP-seq profiles between different experimental conditions or groups.
Folder: H3K27me3
The H3K27me3 folder focuses on the analysis of ChIP-seq data specific to the H3K27me3 epigenetic modification. It includes the following components:
- Data Processing: Scripts and pipelines for preprocessing ChIP-seq data, including read alignment and quality control steps.
- Peak Calling and Filtering: Methods for identifying significant peaks and filtering them based on statistical measures.
- Differential Binding Analysis: Techniques for comparing ChIP-seq profiles between different experimental conditions or groups to identify differentially bound regions.
Folder: Bivalent
The Bivalent folder contains analysis workflows for studying the co-occurrence of H3K4me3 and H3K27me3 modifications, known as bivalent domains. It includes the following components:
- Data Integration: Methods for merging and integrating H3K4me3 and H3K27me3 ChIP-seq data.
- Domain Identification: Tools and approaches for identifying bivalent domains and determining their genomic characteristics.
- Functional Analysis: Scripts for exploring the functional implications and enrichment of genes within bivalent domains.
Folder: Resources
The Resources folder contains supplementary materials and resources that can aid in ChIP-seq analysis, including reference genomes, software packages, and relevant literature.
Feel free to explore the respective folders for more detailed information and specific analysis workflows.
If you would like to contribute to this repository by adding new analysis workflows or improving existing ones, please feel free to submit pull requests. Contributions are highly appreciated!