Second release of the ChIP-seq data analysis training materials from the Harvard Chan Bioinformatics Core (https://bioinformatics.sph.harvard.edu/training). The raw data was obtained from the SRA (https://www.ncbi.nlm.nih.gov/sra?term=SRP134733). Learning Objectives Understand the necessity for, and use of, the command line interface (bash) and HPC for analyzing high-throughput sequencing data. Understand best practices for designing a ChIP-seq experiment and analysis the resulting data. Description This workshop focuses on teaching computational skills to enable the effective use of an high-performance computing environment to implement a ChIP-seq data analysis workflow. In addition to running the workflow from FASTQ files to peak calls, the workshop covers best practice guidelines for ChIP-seq experimental design and data organization/management and data visualization for quality control. Comparison with ATAC-seq and CUT&RUN methods were included in 2022. Introduction to ChIP-seq QC using FASTQC Alignment and filtering of reads (Bowtie2, Samtools) Peak calling (MACS2) Peak overlap (bedtools) Peak visualization (using deepTools)