🧬 TRACK 24 • 4-DAY INTENSIVE
EPIGENOMICS • CHROMATIN DYNAMICS
🧠 HUNTINGTON'S DISEASE CASE STUDY
Chromatin Dynamics • Peak Calling with MACS3 • Differential Binding • Motif Discovery
Epigenomics – ChIP-Seq Data Analysis
From Raw Reads to a Biological Story: Mapping H3K4me3 Promoter Dynamics in Huntington's Disease 🧠🧬
Have ChIP-seq data (or want to work with it) but aren't sure how to get from raw reads to a biological story? In 4 days, you'll run the full pipeline yourself on a real Huntington's Disease dataset 🧠🧬, comparing H3K4me3 promoter marks between HD patients and healthy controls to see how chromatin changes relate to gene dysregulation.
📦 Production Epigenomics & ChIP-Seq Environment
Bioconda + Bioconductor
# Install Complete Epigenomics Toolchain in One Command
conda create -n chipseq_env -c bioconda -c conda-forge \
sra-tools fastqc fastp bowtie2 samtools sambamba bedtools \
macs3 deeptools homer igv r-base bioconductor-diffbind \
bioconductor-deseq2 bioconductor-chipseeker bioconductor-clusterprofiler -y
conda activate chipseq_env
Curriculum Specifications
Track ID
Specialization Track 24
Format & Duration
4 Days • 10 Modules
Core Software
Bowtie2 • MACS3 • DiffBind • deepTools
Biological Model
Huntington's Disease (H3K4me3 Promoters)
Functional Profiling
ChIPseeker • HOMER • IGV Desktop
Academic Access
100% Free & Open Access