<!-- badges: start --> [](https://www.tidyverse.org/lifecycle/#maturing) [](https://opensource.org/licenses/MIT) [](https://github.com/js2264/HiCExperiment/actions/workflows/rworkflows.yml) [](https://js2264.github.io/HiCExperiment) [](https://js2264.github.io/OHCA/) <a href=http://bioconductor.org/packages/release/bioc/html/HiCExperiment.html><img alt="Static Badge" src="https://img.shields.io/badge/Bioc_(release)-Landing_page-green?link=http%3A%2F%2Fbioconductor.org%2FcheckResults%2Fdevel%2Fbioc-LATEST%2FHiCExperiment%2F"></a> <a href=http://bioconductor.org/checkResults/release/bioc-LATEST/HiCExperiment/><img alt="Bioc build (release)" src="https://img.shields.io/badge/dynamic/yaml?url=https%3A%2F%2Fbioconductor.org%2FcheckResults%2Frelease%2Fbioc-LATEST%2FHiCExperiment%2Fraw-results%2Fnebbiolo1%2Fbuildsrc-summary.dcf&query=%24.Status&label=Bioc%20build%20(release)&link=https%3A%2F%2Fbioconductor.org%2FcheckResults%2Frelease%2Fbioc-LATEST%2FHiCExperiment%2F"></a> <a href=http://bioconductor.org/checkResults/devel/bioc-LATEST/HiCExperiment/><img alt="Bioc build (devel)" src="https://img.shields.io/badge/dynamic/yaml?url=https%3A%2F%2Fbioconductor.org%2FcheckResults%2Fdevel%2Fbioc-LATEST%2FHiCExperiment%2Fraw-results%2Fnebbiolo2%2Fbuildsrc-summary.dcf&query=%24.Status&label=Bioc%20build%20(devel)&link=https%3A%2F%2Fbioconductor.org%2FcheckResults%2Fdevel%2Fbioc-LATEST%2FHiCExperiment%2F"></a> <!-- badges: end --> # HiCExperiment [👉 OHCA book 📖](https://js2264.github.io/OHCA/) ---  The `HiCExperiment` package provides a unified data structure to import the three main Hi-C matrix file formats (`.(m)cool`, `.hic` and `HiC-Pro` matrices) in R and performs common array operations on them. The `HiCExperiment` class wraps an (indexed) matrix-like object (i.e. on-disk `.(m)cool`, `.hic` or `HiC-Pro` matrices). For indexed matrices (i.e. `.(m)cool` and `.hic` files), `HiCExperiment` allows one to specfically parse subsets of the contact matrix corresponding to genomic loci of interest, without having to load the entire object in memory. The `HiCExperiment` package also provides methods to import pairs files generated by `pairtools`/`cooler` workflow, by HiC-Pro pipeline, or any type of tabular pairs format (by indicating the columns containing `chr1`, `start1`, `strand1`, `chr2`, `start2`, `strand2` information). `HiCExperiment` S4 class is built on pre-existing Bioconductor classes, namely `BiocFile` and `GInteractions` (Lun, Perry & Ing-Simmons, F1000Research 2016`), and leverages them to point to on-disk Hi-C matrix files and dynamically parse them into R. Several other packages rely on the `HiCExperiment` class to provide a rich ecosystem when interacting with Hi-C data.  ## Installation HiCExperiment is an R/Bioconductor package. As such, it can be installed with: ```r BiocManager::install("HiCExperiment") ``` ## Importing a Hi-C matrix file ### `.(m)cool` files: ```r cool_file <- CoolFile(HiContactsData::HiContactsData('yeast_wt', format = 'cool')) import(cool_file, focus = "II:10000-100000") ``` ``` ## `HiCExperiment` object with 3,454 interactions over 90 regions ## ------- ## fileName: "/home/rsg/.cache/R/ExperimentHub/36d548fb47bf_7751" ## focus: "II:10,000-100,000" ## resolutions(1): 1000 ## current resolution: 1000 ## interactions: 3454 ## scores(2): count balanced ## topologicalFeatures: loops(0) borders(0) compartments(0) viewpoints(0) ## pairsFile: N/A ## metadata(0): ``` ```r mcool_file <- CoolFile(HiContactsData::HiContactsData('yeast_wt', format = 'mcool')) import(mcool_file, focus = "II:10000-100000", resolution = 2000) ``` ``` ## `HiCExperiment` object with 1,004 interactions over 45 regions ## ------- ## fileName: "/home/rsg/.cache/R/ExperimentHub/36d590c5583_7752" ## focus: "II:10,000-100,000" ## resolutions(5): 1000 2000 4000 8000 16000 ## current resolution: 2000 ## interactions: 1004 ## scores(2): count balanced ## topologicalFeatures: loops(0) borders(0) compartments(0) viewpoints(0) ## pairsFile: N/A ## metadata(0): ``` ### `.hic` files: ```r hic_file <- HicFile(HiContactsData::HiContactsData('yeast_wt', format = 'hic')) import(hic_file, focus = "II:10000-100000", resolution = 4000) ``` ``` ## `HiCExperiment` object with 276 interactions over 23 regions ## ------- ## fileName: "/home/rsg/.cache/R/ExperimentHub/7fa45373d163_7836" ## focus: "II:10,000-100,000" ## resolutions(5): 1000 2000 4000 8000 16000 ## current resolution: 4000 ## interactions: 276 ## scores(2): count balanced ## topologicalFeatures: loops(0) borders(0) compartments(0) viewpoints(0) ## pairsFile: N/A ## metadata(0): ``` ### HiC-Pro files: ```r hicpro_file <- HicproFile( HiContactsData::HiContactsData('yeast_wt', format = 'hicpro_matrix'), bed = HiContactsData::HiContactsData('yeast_wt', format = 'hicpro_bed') ) import(hicpro_file) ``` ``` ## `HiCExperiment` object with 2,686,250 interactions over 11,805 regions ## ------- ## fileName: "/home/rsg/.cache/R/ExperimentHub/29210052806_7837" ## focus: "whole genome" ## resolutions(1): 1000 ## current resolution: 1000 ## interactions: 2686250 ## scores(1): counts ## topologicalFeatures: loops(0) borders(0) compartments(0) viewpoints(0) ## pairsFile: N/A ## metadata(1): regions ``` ## Importing a pairs file - `.pairs` files (e.g. from `pairtools` or `cooler`): ```r pairs_file <- PairsFile(HiContactsData('yeast_wt', format = 'pairs.gz')) import(pairs_file) ``` ``` ## GInteractions object with 471364 interactions and 4 metadata columns: ## seqnames1 ranges1 seqnames2 ranges2 | counts frag1 frag2 distance ## <Rle> <IRanges> <Rle> <IRanges> | <integer> <numeric> <numeric> <numeric> ## [1] II 105 --- II 48548 | 1 1358 1681 48443 ## [2] II 113 --- II 45003 | 1 1358 1658 44890 ## [3] II 119 --- II 687251 | 1 1358 5550 687132 ## [4] II 160 --- II 26124 | 1 1358 1510 25964 ## [5] II 169 --- II 39052 | 1 1358 1613 38883 ## ... ... ... ... ... ... . ... ... ... ... ## [471360] II 808605 --- II 809683 | 1 6316 6320 1078 ## [471361] II 808609 --- II 809917 | 1 6316 6324 1308 ## [471362] II 808617 --- II 809506 | 1 6316 6319 889 ## [471363] II 809447 --- II 809685 | 1 6319 6321 238 ## [471364] II 809472 --- II 809675 | 1 6319 6320 203 ## ------- ## regions: 549331 ranges and 0 metadata columns ## seqinfo: 1 sequence from an unspecified genome; no seqlengths ``` - `.validPairs` files (e.g. from HiC-Pro pipeline): ```r hicpro_pairs_file <- PairsFile(HiContactsData('yeast_wt', format = 'hicpro_pairs')) import(hicpro_pairs_file, nrows = 100) ``` ``` ## GInteractions object with 100 interactions and 4 metadata columns: ## seqnames1 ranges1 seqnames2 ranges2 | counts frag1 frag2 distance ## <Rle> <IRanges> <Rle> <IRanges> | <integer> <numeric> <character> <numeric> ## [1] I 33 --- I 620 | 1 414 HIC_I_1 587 ## [2] I 35 --- III 301620 | 1 336 HIC_I_1 NA ## [3] I 41 --- I 68853 | 1 352 HIC_I_1 68812 ## [4] I 49 --- I 3233 | 1 311 HIC_I_1 3184 ## [5] I 51 --- VIII 197898 | 1 397 HIC_I_1 NA ## ... ... ... ... ... ... . ... ... ... ... ## [96] I 138 --- VIII 326284 | 1 251 HIC_I_1 NA ## [97] I 141 --- I 2466 | 1 231 HIC_I_1 2325 ## [98] I 142 --- I 2219 | 1 278 HIC_I_1 2077 ## [99] I 142 --- XI 222517 | 1 270 HIC_I_1 NA ## [100] I 142 --- XV 441757 | 1 280 HIC_I_1 NA ## ------- ## regions: 158 ranges and 0 metadata columns ## seqinfo: 15 sequences from an unspecified genome; no seqlengths ``` ## The `HiCExperiment` ecosystem ### HiContacts [`HiContacts` package](http://www.bioconductor.org/packages/release/bioc/html/HiContacts.html) further provides **analytical** and **visualization** tools to investigate Hi-C matrices imported as `HiCExperiment` in R. Among other features, it provides the end-user with generic functions to annotate topological features in a Hi-C contact map and export them, notably compartments, domains of constrained interactions (so-called TADs) and focal chromatin loops. ### HiCool `HiCool` package integrates an end-to-end processing workflow, to generate multi-resolution balanced contact matrices from paired-end fastq files of Hi-C experiments. Under the hood, `HiCool` leverages `hicstuff` and `cooler` to process fastq files into .mcool files. [`hicstuff`](https://github.com/koszullab/hicstuff) takes care of the heavy-lifting, and accurately filters non-informative read pairs out, to retain only informative contacts. Two important features of `HiCool` are: 1. Its operability within the `R` ecosystem. It relies on `basilisk` to set up a `conda` environment with pinned versions of each software it needs to align, filter and process read pairs into contact matrices. 2. Its transparency. `HiCool` generates QC checks and logs, all embedded in HTML files to easily inspect the quality of each sample. ### fourDNData `fourDNData` (read `"4DN Data"`) provides a gateway to the [4DN data portal](https://data.4dnucleome.org/). ### HiContactsData [`HiContactsData` package](http://www.bioconductor.org/packages/release/bioc/html/HiContactsData.html) provides toy datasets to illustrate how the `HiCExperiment` ecosystem works. ## Contributing We use [devtools](https://github.com/r-lib/devtools) and [testthat](https://github.com/r-lib/testthat) for the development workflow. A Makefile is provided for automation. New functions should be documented with [roxygen2](https://github.com/r-lib/roxygen2) comments and associated tests should be added inside `tests/testthat/`. * To install the package for development, run `make install`. * To run tests, run `make test` * To know more, run `make help` For development purposes, we provide a DockerHub-hosted `docker` image with `HiCExperiment` and related packages pre-installed and ready-to-go. A new image is automatically built on every `push`. ```sh ## To fetch the latest docker image from Docker Hub (for development purposes!) docker pull js2264/hicexperiment:latest ## To start docker image docker run -it js2264/hicexperiment:latest /usr/local/bin/R ``` On top of that, for each release, an extra `docker` image is built and uploaded to the Github Container Repository. ```sh ## To fetch release-specific docker image from Github Container Repo docker pull ghcr.io/js2264/hicexperiment:0.99.9 ## To start docker image docker run -it ghcr.io/js2264/hicexperiment:0.99.9 /usr/local/bin/R ```