Hi-C-analysis

• This repository is for analyzing the Hi-C data.

• Use this script pre_environment.sh to prepare the analysis environment.

Hi-C data compare tools

➡️ diffHic

• Detects differential interactions across biological conditions in a Hi-C experiment. Methods are provided for read alignment and data pre-processing into interaction counts. Statistical analysis is based on edgeR and supports normalization and filtering. Several visualization options are also available.
• Citation (from within R, enter citation("diffHic")):

Lun ATL, Smyth GK (2015). “diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data.” BMC Bioinformatics, 16, 258.

• Installation To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("diffHic")

➡️ multiHiCcompare

• Github

• Tutorial

• HiCcompareWorkshop

• Citation (from within R, enter citation("multiHiCcompare")):

Stansfield JC, Cresswell KG, Dozmorov MG (2019). “multiHiCcompare: joint normalization and comparative analysis of complex Hi-C experiments.” Bioinformatics, 35(17). doi:10.1093/bioinformatics/btz048, https://github.com/dozmorovlab/multiHiCcompare.

• Installation To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("multiHiCcompare")