HiCcompareWorkshop introduces methods for the comparative (aka differential) analysis of the three-dimensional (3D) structure of the genome using data generated by high-throughput chromatin conformation capture (Hi-C) technologies. Hi-C data allows for insights into the genome-wide 3D genomic interactions which play an important role in regulating gene expression and other genomic processes. Just as differential expression analyses using RNA-seq data have become a routine part of genomic experiments, we expect the differential analysis of genomic interactions to become a common task. This workflow will help a novice learn to perform differential analysis of two or more Hi-C datasets and interpret the differential genomic interactions’ results.

This workshop is based on Stansfield et al., “R Tutorial: Detection of Differentially Interacting Chromatin Regions From Multiple Hi-C Datasets.”.

This workshop will be presented at the Bioconductor Virtual Conference 2020, July 30, 2020, 10:00-10:55am

Using Docker

The easiest way to get started with the workshop is to run it from a Docker container.

Pull the latest version of the HiCcompareWorkshop Docker image, docker pull mdozmorov/hiccompareworkshop:latest
Run docker run -e PASSWORD=yourpassword -p 8787:8787 -d --rm mdozmorov/hiccompareworkshop. Use -v $(pwd):/home/rstudio argument to map your local directory to the container.
Log in to RStudio at http://localhost:8787 using username rstudio and password yourpassword. Note that on Windows you need to provide your localhost IP address like http://191.163.92.108:8787/ - find it using docker-machine ip default in Docker’s terminal.
Run browseVignettes(package = "HiCcompareWorkshop"). Click on one of the links, “HTML”, “source”, “R code”.
- In case of The requested page was not found error, add help/ to the URL right after the hostname, e.g., http://localhost:8787/help/library/HiCcompareWorkshop/doc/hic_tutorial.html. This is a known bug.

Local Installation

if(!require(devtools)) install.packages("devtools")
devtools::install_github(repo = "mdozmorov/HiCcompareWorkshop", build_vignettes = TRUE)

If installation fails due to missing packages, install them as follows:

if(!require(BiocManager)) install.packages("BiocManager")
BiocManager::install(c('edgeR', 'HiCcompare', 'multiHiCcompare', 'clusterProfiler', 'ROntoTools'))

Workshop Description

Instructor name and contact information

Mikhail Dozmorov (mikhail.dozmorov@vcuhealth.org)

Pre-requisites

Basic knowledge of R syntax and command-line tools
Familiarity with Hi-C chromatin conformation capture technology
Understanding of Hi-C data properties (distance-dependent decay of interaction frequencies, biases)
Familiarity with specialized (.hic http://aidenlab.org/data.html, .cool ftp://cooler.csail.mit.edu/coolers) and text-based (sparse upper-triangular, full square matrix) Hi-C data formats is desirable

R / Bioconductor packages used

Time outline

The workshop duration is 55 min. Approximate timing of activities:

Activity	Time
Overview	5m
Data representation and manipulation	10m
Differential analysis of Hi-C data	10m
Interpretation of Hi-C differences	15m
Questions and answers session	15m

Learning Goals

Get familiar with Hi-C data import into R
Understand the visualization of biases between pairs of Hi-C datasets using Mean-Distance (MD) plot
Learn the Loess-based normalization strategy that minimizes between-dataset differences
Perform differential analysis of 2 × 2 groups of Hi-C data, accounting for covariates, if needed
Visualize and understand interaction frequency differences
Get familiar with approaches for interpretation of chromatin interaction differences in the context of genes and gene expression differences

Detection of Differentially Interacting Chromatin Regions From Multiple Hi-C Datasets