This repository provides a comprehensive suite of bioinformatics pipelines tailored for various high-throughput sequencing data types. The goal of this project is to serve as an educational resource for a course that covers the following data types and methodologies:
- RNA-seq
- ATAC-seq
- Single-cell sequencing
- Multiome analysis
- DNA methylation analysis
- Spatial Transcriptomics
Each directory within this repository is devoted to one of these data types, containing relevant scripts, workflows, and example data.
The course is divided into several modules, each focusing on a different aspect of bioinformatics analysis:
- Quality control and preprocessing of count data
- Quantification of gene expression
- Differential expression analysis
- Functional enrichment and pathway analysis
- Data preprocessing and quality control
- Peak calling and annotation
- Integration with gene expression data
- Visualization of ATAC-seq data
- Preprocessing of scRNA-seq data
- Clustering and identifying cell populations
- Differential expression analysis in single cells
- Pseudotime analysis
- Data integration strategies
- Multiomics data visualization
- Case studies in multiomics analysis
- Processing methylation data
- Identification of differentially methylated regions (DMRs)
- Integration with gene expression data
- Methylation's role in gene regulation
- Processing ST data
- Quality Control
- Differential Expression Analysis
- Comparison report
Both individual and group projects are included in this course to provide hands-on experience with real-world data. These projects reinforce the concepts and techniques covered in the lectures and practical sessions.
Each data type has its directory:
RNA-seq/ATAC-seq/Single-cell/Multiome/Methylation/Spatial Transcriptomics/