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HiContacts

Analyzing Hi-C data in R with HiCExperiment objects

https://github.com/js2264/hicontacts

Science Score: 46.0%

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bioconductor-package gene grna-sequence immune-repertoire genomics ontology sequencing
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Repository

Analyzing Hi-C data in R with HiCExperiment objects

Basic Info
Statistics
  • Stars: 14
  • Watchers: 1
  • Forks: 3
  • Open Issues: 4
  • Releases: 0
Created almost 5 years ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

DOI rworkflows Documentation OHCA book Static Badge Bioc build (release) Bioc build (devel) <!-- badges: end -->

HiContacts

👉 OHCA book 📖

Please cite:

Serizay J, Matthey-Doret C, Bignaud A, Baudry L, Koszul R (2024). “Orchestrating chromosome conformation capture analysis with Bioconductor.” Nature Communications, 15, 1-9. doi:10.1038/s41467-024-44761-x.

DOI

HiContacts provides tools to investigate (m)cool matrices imported in R by HiCExperiment.

It leverages the HiCExperiment class of objects, built on pre-existing Bioconductor objects, namely InteractionSet, GInterations and ContactMatrix (Lun, Perry & Ing-Simmons, F1000Research 2016), and provides analytical and visualization tools to investigate contact maps.

Installation

HiContacts is available in Bioconductor. To install the current release, use:

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

To install the most recent version of HiContacts, you can use:

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

Citation

If you are using HiContacts in your research, please cite:

Serizay J (2022). HiContacts: HiContacts: R interface to cool files. R package version 1.1.0 https://github.com/js2264/HiContacts.

How to use HiContacts

HiContacts includes a introduction vignette where its usage is illustrated. To access the vignette, please use:

r vignette('HiContacts')

Visualising Hi-C contact maps and features

Importing a Hi-C contact maps file with HiCExperiment

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

Plotting matrices (square or horizontal)

r 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

r 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)

r 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

```r microCmcool <- fourDNData::fourDNData('4DNES14CNC1I', 'mcool') hic <- import(microCmcool, format = 'mcool', resolution = 10000000) genome <- BSgenome.Mmusculus.UCSC.mm10::BSgenome.Mmusculus.UCSC.mm10

- Get compartments

hic <- getCompartments( hic, resolution = 100000, genome = genome, chromosomes = c('chr17', 'chr19') )

- Export compartments as bigwig and bed files

export(IRanges::coverage(metadata(hic)$eigens, weight = 'eigen'), 'microCcompartments.bw') export( topologicalFeatures(hic, 'compartments')[topologicalFeatures(hic, 'compartments')$compartment == 'A'], 'microCA-compartments.bed' ) export( topologicalFeatures(hic, 'compartments')[topologicalFeatures(hic, 'compartments')$compartment == 'B'], 'microC_B-compartments.bed' )

- Generate saddle plot

plotSaddle(hic) ```

Diamond insulation score and chromatin domains borders

```r

- Compute insulation score

hic <- refocus(hic, 'chr19:1-30000000') |> zoom(resolution = 10000) |> getDiamondInsulation(window_size = 100000) |> getBorders()

- Export insulation as bigwig track and borders as bed file

export(IRanges::coverage(metadata(hic)$insulation, weight = 'insulation'), 'microCinsulation.bw') export(topologicalFeatures(hic, 'borders'), 'microCborders.bed') ```

In-depth analysis of HiCExperiment objects

Arithmetics

Detrend

Autocorrelate

Divide

Merge

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

r 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

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

Cis-trans ratios

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

Scalograms

```r

```

HiCExperiment ecosystem

HiCool is integrated within the HiCExperiment ecosystem in Bioconductor. Read more about the HiCExperiment class and handling Hi-C data in R here.

  • HiCExperiment: Parsing Hi-C files in R
  • HiCool: End-to-end integrated workflow to process fastq files into .cool and .pairs files
  • HiContacts: Investigating Hi-C results in R
  • HiContactsData: Data companion package
  • fourDNData: Gateway package to 4DN-hosted Hi-C experiments

Owner

  • Name: Jacques Serizay
  • Login: js2264
  • Kind: user
  • Location: Paris, FR

GitHub Events

Total
  • Issues event: 4
  • Watch event: 3
  • Issue comment event: 5
  • Push event: 5
  • Fork event: 1
Last Year
  • Issues event: 4
  • Watch event: 3
  • Issue comment event: 5
  • Push event: 5
  • Fork event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 219
  • Total Committers: 3
  • Avg Commits per committer: 73.0
  • Development Distribution Score (DDS): 0.018
Past Year
  • Commits: 85
  • Committers: 3
  • Avg Commits per committer: 28.333
  • Development Distribution Score (DDS): 0.047
Top Committers
Name Email Commits
js2264 j****y@g****m 215
J Wokaty j****y@s****u 2
J Wokaty j****y 2
Committer Domains (Top 20 + Academic)
sph.cuny.edu: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 16
  • Total pull requests: 0
  • Average time to close issues: 2 months
  • Average time to close pull requests: N/A
  • Total issue authors: 14
  • Total pull request authors: 0
  • Average comments per issue: 2.81
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 8
  • Pull requests: 0
  • Average time to close issues: about 1 month
  • Average time to close pull requests: N/A
  • Issue authors: 7
  • Pull request authors: 0
  • Average comments per issue: 1.25
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • xiasijian (2)
  • LiNk-NY (1)
  • ggmirizio (1)
  • narzouni (1)
  • GuidoBarzaghi (1)
  • mannekim (1)
  • hackkr (1)
  • matteozoia4 (1)
  • ratheraarif (1)
  • evaham1 (1)
  • PengfeiInTuebingen (1)
  • rpetroll (1)
  • xl5525 (1)
Pull Request Authors
Top Labels
Issue Labels
stale (2)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 8,528 total
  • Total dependent packages: 2
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 1
bioconductor.org: HiContacts

Analysing cool files in R with HiContacts

  • Versions: 5
  • Dependent Packages: 2
  • Dependent Repositories: 0
  • Downloads: 8,528 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Average: 30.1%
Downloads: 90.4%
Maintainers (1)
jacquesserizay@gmail.com
Last synced: 7 months ago

Dependencies

DESCRIPTION cran
  • R >= 4.2 depends
  • BiocParallel * imports
  • GenomeInfoDb * imports
  • GenomicInteractions * imports
  • GenomicRanges * imports
  • HiContactsData * imports
  • IRanges * imports
  • InteractionSet * imports
  • Matrix * imports
  • S4Vectors * imports
  • corrr * imports
  • data.table * imports
  • dplyr * imports
  • ggplot2 * imports
  • ggrastr * imports
  • glue * imports
  • methods * imports
  • plyranges * imports
  • purrr * imports
  • reticulate * imports
  • rhdf5 * imports
  • scales * imports
  • stringr * imports
  • tibble * imports
  • tidyr * imports
  • tools * imports
  • zeallot * imports
  • cowplot * suggests
  • knitr * suggests
  • testthat >= 3.0.0 suggests
.github/workflows/rworkflows.yml actions
  • neurogenomics/rworkflows master composite