HiContacts

Installation

if (!requireNamespace("BiocManager",quietly=TRUE))    install.packages("BiocManager")BiocManager::install("HiContacts")

install.packages("devtools")devtools::install_github("js2264/HiContacts")library(HiContacts)

Citation

How to useHiContacts

vignette('HiContacts')

Visualising Hi-C contact maps and features

Importing a Hi-C contact maps file withHiCExperiment

mcool_file<-HiContactsData::HiContactsData('yeast_wt',format='mcool')range<-'I:20000-80000'# range of interestavailableResolutions(mcool_file)hic<-HiCExperiment::import(mcool_file,format='mcool',focus=range,resolution=1000)hic

Plotting matrices (square or horizontal)

plotMatrix(hic,use.scores='count')plotMatrix(hic,use.scores='balanced',limits= c(-4,-1))plotMatrix(hic,use.scores='balanced',limits= c(-4,-1),maxDistance=100000)

Plotting matrices with topological features

library(rtracklayer)mcool_file<-HiContactsData::HiContactsData('yeast_wt',format='mcool')hic<- import(mcool_file,format='mcool',focus='IV')loops<- system.file("extdata",'S288C-loops.bedpe',package='HiContacts')|>     import()|>InteractionSet::makeGInteractionsFromGRangesPairs()borders<- system.file("extdata",'S288C-borders.bed',package='HiContacts')|>     import()p<- plotMatrix(hic,loops=loops,borders=borders,limits= c(-4,-1),dpi=120)

Plotting aggregated matrices (a.k.a. APA plots)

contacts<- contacts_yeast()contacts<- zoom(contacts,resolution=2000)aggr_centros<- aggregate(contacts,targets= topologicalFeatures(contacts,'centromeres'))plotMatrix(aggr_centros,use.scores='detrended',limits= c(-1,1),scale='linear')

Mapping topological features

Chromosome compartments

microC_mcool<-fourDNData::fourDNData('4DNES14CNC1I','mcool')hic<- import(microC_mcool,format='mcool',resolution=10000000)genome<-BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10# - Get compartmentshic<- getCompartments(hic,resolution=100000,genome=genome,chromosomes= c('chr17','chr19'))# - Export compartments as bigwig and bed filesexport(IRanges::coverage(metadata(hic)$eigens,weight='eigen'),'microC_compartments.bw')export(    topologicalFeatures(hic,'compartments')[topologicalFeatures(hic,'compartments')$compartment=='A'],'microC_A-compartments.bed')export(    topologicalFeatures(hic,'compartments')[topologicalFeatures(hic,'compartments')$compartment=='B'],'microC_B-compartments.bed')# - Generate saddle plotplotSaddle(hic)

Diamond insulation score and chromatin domains borders

# - Compute insulation scorehic<- refocus(hic,'chr19:1-30000000')|>     zoom(resolution=10000)|>     getDiamondInsulation(window_size=100000)|>     getBorders()# - Export insulation as bigwig track and borders as bed fileexport(IRanges::coverage(metadata(hic)$insulation,weight='insulation'),'microC_insulation.bw')export(topologicalFeatures(hic,'borders'),'microC_borders.bed')

In-depth analysis ofHiCExperiment objects

Arithmetics

Detrend

Autocorrelate

Divide

Merge

Distance law, a.k.a. P(s)

hic<- import(CoolFile(mcool_file,pairs=HiContactsData::HiContactsData('yeast_wt',format='pairs.gz')))ps<- distanceLaw(hic)plotPs(ps,ggplot2::aes(x=binned_distance,y=norm_p))

Virtual 4C

hic<- import(CoolFile(mcool_file))v4C<- virtual4C(hic,viewpoint= GRanges('V:150000-170000'))plot4C(v4C)

Cis-trans ratios

hic<- import(CoolFile(mcool_file))cisTransRatio(hic)

Scalograms

HiCExperiment ecosystem