Day 1 - Gene expression analysis
- Lecture 1: General processing of NGS data
- Lab 1: Hands-on processing of RNA-seq data using FastQC, trim_galore, and alignment.
- Lecture 2: Quantification of gene expression
- Lab 2: Quantification and differential gene expression by RNA-seq
Day 2 - Chromatin accessibility
- Lecture 3: Introduction to general epigenomics concepts
- Lab 3: Processing MNase-seq data
- Lecture 4: Peak calling and accessibility visualization
- Lab 4: ATAC-seq peak calling and analysis
Day 3 - Chromatin composition
- Lecture 5: Introduction to ChIP-seq
- Lab 5: Integrating ChIP-seq peaks and genomic annotations
- Lecture 6: DNA motif methodologies and resources
- Lab 6: Meme and TFBSTools for motif enrichment analysis in R
Day 4 - Chromatin interactions
- Lecture 7: Profiling chromatin contacts and visualize Hi-C data
- Lab 7: Alignments and quality assessment using hicstuff
- Lecture 8: Identifying structural features from Hi-C data
- Lab 8: Levering chromosight to study chromatin contacts
Day 5 - Data integration and multi-omics
- Lecture 9: Integrating multi-omics data through GO analysis
- Lab 9: Combining RNA-seq, ATAC-seq, ChIP-seq and Hi-C data with Bioconductor
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