Epigenomics Data Analysis Epigenomics Data Analysis 20 Demo 5 - Leveraging Bioconductor resources 18 Lecture 10 - HiC processing Welcome Program RStudio Prerequisites Day 1 1 Lecture 1 - Introduction to epigenomics data analysis 2 Lecture 2 - General processing of genome-wide epigenomic assays 3 Demo 1 - Processing of MNase-seq data 4 Lab 1 - Processing of MNase-seq data Day 2 5 Lecture 3 - NGS processing workflows 6 Lecture 4 - ATAC-seq processing and analyis 7 Lecture 5 - R 101 8 Demo 2 - Processing of ATAC-seq data 9 Lab 2 - ATAC-seq downstream analysis Day 3 10 Lecture 6 - ChIP-seq processing and analyis 11 Lecture 7 - R 201 12 Demo 3 - Processing of ChIP-seq data 13 Lab 3 - ChIP-seq downstream analysis Day 4 14 Lecture 8 - RNA-seq processing and analyis 15 Lecture 9 - R 301 16 Demo 4 - Processing of RNA-seq data 17 Lab 4 - RNA-seq downstream analysis Day 5 18 Lecture 10 - HiC processing 19 Lecture 11 - GO and GSEA analysis 20 Demo 5 - Leveraging Bioconductor resources 21 Lab 5 - Multi-omics data integration Extra resources Epigenomics Data Analysis |
J. Serizay This book was built with Quarto. Day 5 19 Lecture 11 - GO and GSEA analysis