multi-omics-integrationlisted

# Multi-Omics Integration of ENCODE Data ## When to Use - User wants to integrate multiple ENCODE data types (RNA-seq + ATAC-seq + ChIP-seq) for a tissue - User asks about "multi-omics", "integrative analysis", "regulatory landscape", or "layer epigenomic data" - User needs to build a comprehensive view of active enhancers, promoters, and TF binding in a tissue - User wants to combine expression with chromatin state to identify cell-type-specific regulatory networks - Example queries: "integrate all ENCODE data for pancreas", "build a regulatory landscape for liver", "combine RNA-seq and ChIP-seq to find active enhancers" Layer RNA-seq, ATAC-seq, Histone ChIP-seq, and TF ChIP-seq data from ENCODE to build a comprehensive regulatory landscape for a tissue or cell type. ## Scientific Rationale **The question**: "What regulatory elements are active in my tissue, and how do expression, chromatin accessibility, histone marks, and TF binding converge to define cell identity?" No single assay captures the full picture of gene regulation. RNA-seq tells you **what** is expressed. ATAC-seq tells you **where** chromatin is open. Histone ChIP-seq tells you **how** chromatin is modified. TF ChIP-seq tells you **who** is binding. Each assay provides one dimension; integrating them reveals the regulatory logic. ### The Framework (Mawla, van der Meulen & Huising 2023) Mawla et al. (2023, BMC Genomics) demonstrated this integrative approach by comparing ATAC-seq chromatin accessibilit