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 will be presented at the Bioconductor Virtual Conference 2020, July 30, 2020, 10:00-10:55am
The easiest way to get started with the workshop is to run it from a Docker container.
docker pull mdozmorov/hiccompareworkshop:latest
docker run -e PASSWORD=yourpassword -p 8787:8787 -d --rm mdozmorov/hiccompareworkshop. Use
-v $(pwd):/home/rstudioargument to map your local directory to the container.
yourpassword. Note that on Windows you need to provide your localhost IP address like
http://188.8.131.52:8787/- find it using
docker-machine ip defaultin Docker’s terminal.
browseVignettes(package = "HiCcompareWorkshop"). Click on one of the links, “HTML”, “source”, “R code”.
The requested page was not founderror, 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.
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'))
.coolftp://cooler.csail.mit.edu/coolers) and text-based (sparse upper-triangular, full square matrix) Hi-C data formats is desirable
The workshop duration is 55 min. Approximate timing of activities:
|Data representation and manipulation||10m|
|Differential analysis of Hi-C data||10m|
|Interpretation of Hi-C differences||15m|
|Questions and answers session||15m|