Computational Methods for 3D Genome Analysis

This volume covers the latest methods and analytical approaches used to study the computational analysis of three-dimensional (3D) genome structure. The chapters in this book are organized into six parts. Part One discusses different NGS assays and the regulatory mechanism of 3D genome folding by SMC complexes. Part Two presents analysis workflows for Hi-C and Micro-C in different species, including human, mouse, medaka, yeast, and prokaryotes. Part Three covers methods for chromatin loop detection, sub-compartment detection, and 3D feature visualization. Part Four explores single-cell Hi-C and the cell-to-cell variability of the dynamic 3D structure. Parts Five talks about the analysis of polymer modelling to simulate the dynamic behavior of the 3D genome structure, and Part Six looks at 3D structure analysis using other omics data, including prediction of 3D genome structure from the epigenome, double-strand break-associated structure, and imaging-based 3D analysis using seqFISH. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and tools, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Cutting-edge and thorough, Computational Methods for 3D Genome Analysis: Methods and Protocols is a valuable resource for researchers interested in using computational methods to further their studies in the nature of 3D genome organization.

Methods for Genome-Wide Chromatin Interaction Analysis.- Structural Maintenance of Chromosomes Complexes.- Read Mapping for Hi-C Analysis.- Micro-C Analysis Workflow using Pairtools and Juicer.- HOMER for Analysis of Hi-C Data and Assessment of Composite Structure of the X Chromosome.- CWL-Based Analysis Pipeline for Hi-C Data: From FASTQ Files to Matrices.- Acquisition and Analysis Methods for Hi-C Data from Medaka Early Embryos.- Step-by-Step Protocol to Generate Hi-C Contact Maps Using the rfy_hic2 Pipeline.- Hi-C/3C-seq Data Analysis for Prokaryotic Genomes with HiC-Pro.- Exploring Contact Distance Distributions with Google Colaboratory.- Supervised Chromatin Loop Detection using Peakachu Version 2.- Systematic Inference of Multi-Scale Chromatin Sub-Compartments using Calder2.- Analysis and Visualization of Multiple Hi-C and Micro-C Data with CustardPy.- Single-Cell Hi-C Analysis Workflow with Pairtools.- Reconstruction of 3D Chromosome Structure from Single Cell Hi-C Data via Recurrence Plots.- 4D Genome Analysis using PHi-C2.- Construction of Coarse-Grained Molecular Dynamics Model of Nuclear Global Chromosomes Dynamics in Mammalian Cells.- Three-Dimensional Simulation of Whole-Genome Structuring through the Transition from Anaphase to Interphase.- Integrative Modeling of 3D Genome Organization by Bayesian Molecular Dynamics Simulations with Hi-C Metainference.- Prediction of Enhancer-Gene Interactions using Chromatin-Conformation Capture and Epigenome Data using STARE.- Learning Enhancer-Gene Associations from Bulk Transcriptomic and Epigenetic Sequencing Data with STITCHIT.- Machine and Deep Learning Methods for Predicting 3D Genome Organization.- Processing and Visualization of Protec-Seq Data for the Generation of Calibrated, Genome-Wide Double DSB (Double Strand Break) Maps.- Image Analysis Protocol for DNA/RNA/Immunofluorescence (IF)-seqFISH Data.- Extracting Chromosome Structural Information as One-Dimensional Metrics and Integrating Them with Epigenomics.- Exploring Cohesin-Related Multiomics Information in the Web Browser.