library(ggplot2)
library(GenomicRanges)
## Loading required package: stats4
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## Loading required package: IRanges
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library(InteractionSet)
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## Loading required package: Biobase
## Welcome to Bioconductor
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library(HiCExperiment)
## Consider using the `HiContacts` package to perform advanced genomic operations
## on `HiCExperiment` objects.
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## https://js2264.github.io/OHCA/
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library(fourDNData)
library(DNAZooData)
library(rtracklayer)8 Data gateways: accessing public Hi-C data portals
Pre-loading packages and objects π¦
Aims
This chapter focuses on introducing two important portals hosting public Hi-C datasets: the 4DN Consortium and the DNA Zoo project. Two R packages provide a programmatic access to these portals:
fourDNDataDNAZooData
The Hi-C experimental approach has gained significant traction across multiple fields related to genome biology, and several consortia developed large-scale programs based on this technique. The fourDNData and DNAZooData R packages were designed to accelerate the investigation of chromatin structure using these public resources.
8.1 4DN data portal
The 4D Nucleome Data Coordination and Integration Center (DCIC) has developed and actively maintains a data portal providing public access to a wealth of resources to investigate 3D chromatin architecture. Notably, 3D chromatin conformation libraries relying on different technologies (βin situβ or βdilutionβ Hi-C, Capture Hi-C, Micro-C, DNase Hi-C, β¦), generated by 50+ collaborating labs, were homogeneously processed, yielding more than 350 sets of processed files.
fourDNData (read 4DN-Data) is a package giving programmatic access to these uniformly processed Hi-C contact files.
The fourDNData() function provides a gateway to 4DN-hosted Hi-C files, including contact matrices (in .hic or .mcool) and other Hi-C derived files such as annotated compartments, domains, insulation scores, or .pairs files.
library(fourDNData)
head(fourDNData())
## experimentSetAccession fileType size organism experimentType
## 1 4DNES18BMU79 pairs 10151.53 mouse in situ Hi-C
## 3 4DNES18BMU79 hic 5285.82 mouse in situ Hi-C
## 4 4DNES18BMU79 mcool 6110.75 mouse in situ Hi-C
## 5 4DNES18BMU79 boundaries 0.12 mouse in situ Hi-C
## 6 4DNES18BMU79 insulation 7.18 mouse in situ Hi-C
## 7 4DNES18BMU79 compartments 0.18 mouse in situ Hi-C
## details dataset
## 1 DpnII Hi-C on Mouse Olfactory System cells
## 3 DpnII Hi-C on Mouse Olfactory System cells
## 4 DpnII Hi-C on Mouse Olfactory System cells
## 5 DpnII Hi-C on Mouse Olfactory System cells
## 6 DpnII Hi-C on Mouse Olfactory System cells
## 7 DpnII Hi-C on Mouse Olfactory System cells
## condition
## 1 Mature olfactory sensory neurons with conditional Ldb1 knockout
## 3 Mature olfactory sensory neurons with conditional Ldb1 knockout
## 4 Mature olfactory sensory neurons with conditional Ldb1 knockout
## 5 Mature olfactory sensory neurons with conditional Ldb1 knockout
## 6 Mature olfactory sensory neurons with conditional Ldb1 knockout
## 7 Mature olfactory sensory neurons with conditional Ldb1 knockout
## biosource biosourceType publication
## 1 olfactory receptor cell primary cell Monahan K et al. (2019)
## 3 olfactory receptor cell primary cell Monahan K et al. (2019)
## 4 olfactory receptor cell primary cell Monahan K et al. (2019)
## 5 olfactory receptor cell primary cell Monahan K et al. (2019)
## 6 olfactory receptor cell primary cell Monahan K et al. (2019)
## 7 olfactory receptor cell primary cell Monahan K et al. (2019)
## URL
## 1 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/49504f97-904e-48c1-8c20-1033680b66da/4DNFIC5AHBPV.pairs.gz
## 3 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/6cd4378a-8f51-4e65-99eb-15f5c80abf8d/4DNFIT4I5C6Z.hic
## 4 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/01fb704f-2fd7-48c6-91af-c5f4584529ed/4DNFIVPAXJO8.mcool
## 5 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/5c07cdee-53e2-43e0-8853-cfe5f057b3f1/4DNFIR3XCIMA.bed.gz
## 6 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/d1f4beb9-701f-4188-abe2-6271fe658770/4DNFIXKKNMS7.bw
## 7 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/3d429647-51c8-4e3a-a18b-eec0b1480905/4DNFIN13N8C1.bw8.1.1 Querying individual files
The fourDNData() function can be used to directly fetch specific files from the 4DN data portal:
cf <- fourDNData(experimentSetAccession = '4DNESJNPEKZD', type = 'mcool')This effectively downloads and caches the queried file locally.
cf
## [1] "/root/.cache/R/fourDNData/150e6c94d4df_4DNFIZL8OZE1.mcool"
availableChromosomes(cf)
## Seqinfo object with 24 sequences from an unspecified genome:
## seqnames seqlengths isCircular genome
## chr1 248956422 <NA> <NA>
## chr2 242193529 <NA> <NA>
## chr3 198295559 <NA> <NA>
## chr4 190214555 <NA> <NA>
## chr5 181538259 <NA> <NA>
## ... ... ... ...
## chr20 64444167 <NA> <NA>
## chr21 46709983 <NA> <NA>
## chr22 50818468 <NA> <NA>
## chrX 156040895 <NA> <NA>
## chrY 57227415 <NA> <NA>
availableResolutions(cf)
## resolutions(13): 1000 2000 ... 5e+06 1e+07
##
import(cf, focus = "chr4:10000001-20000000", resolution = 5000)
## `HiCExperiment` object with 656 contacts over 2,000 regions
## -------
## fileName: "/root/.cache/R/fourDNData/150e6c94d4df_4DNFIZL8OZE1.mcool"
## focus: "chr4:10,000,001-20,000,000"
## resolutions(13): 1000 2000 ... 5000000 10000000
## active resolution: 5000
## interactions: 614
## scores(2): count balanced
## topologicalFeatures: compartments(0) borders(0) loops(0) viewpoints(0)
## pairsFile: N/A
## metadata(0):Different Hi-C related genomic files are provided by the 4DN consortium. The type of file to fetch can be specified with the type argument:
-
type = 'pairs'will fetch the pairs file which was generated by the 4DN consortium and binned into a contact matrix. Once fetched from the 4DN data portal, the local file can be imported inRusing theimportfunction, which will generate aGInteractionsobject.
## Not evaluated for now
pairs_f <- fourDNData(experimentSetAccession = '4DNESJNPEKZD', type = 'pairs')
print(pairs_f)
import(pairs_f)
Watch out
.pairs files can be particularly large and therefore will take both and long time to download and a large storage footprint.
-
type = 'insulation'will fetch a.bigwigtrack file precomputed by the 4DN consortium. This track corresponds to the genome-wide insulation score computed bycooltoolsas described in Crane et al. (2015). To know more about this, read the excerpt from 4DN data portal. Once fetched from the 4DN data portal, the local file can be imported inRusing theimportfunction, which will generate aRleListobject.
library(rtracklayer)
fourDNData(experimentSetAccession = '4DNES25ABNZ1', type = 'insulation') |>
import(as = 'Rle')
## RleList of length 21
## $chr1
## numeric-Rle of length 195471971 with 38145 runs
## Lengths: 3065000 5000 ... 5000 171971
## Values : 0.00000e+00 1.01441e-01 ... 0.807009 0.000000
##
## $chr10
## numeric-Rle of length 130694993 with 25100 runs
## Lengths: 3175000 5000 5000 ... 5000 169993
## Values : 0.00000000 0.37584546 0.33597839 ... 0.628601 0.000000
##
## $chr11
## numeric-Rle of length 122082543 with 23536 runs
## Lengths: 3165000 5000 5000 ... 5000 162543
## Values : 0.0000000 -0.7906257 -0.7930040 ... 0.515919 0.000000
##
## $chr12
## numeric-Rle of length 120129022 with 22578 runs
## Lengths: 3075000 5000 5000 ... 5000 5000 164022
## Values : 0.000000 0.411216 0.400357 ... 0.1650951 0.2175749 0.0000000
##
## $chr13
## numeric-Rle of length 120421639 with 22807 runs
## Lengths: 3080000 5000 5000 ... 5000 171639
## Values : 0.00000000 0.17005745 0.10652249 ... 1.14856148 0.00000000
##
## ...
## <16 more elements>-
type = 'boundaries'will fetch a.bedfile precomputed by the 4DN consortium, listing the annotated borders between topological domains. These borders correspond to local minima identified from the genome-wide insulation track. It can also be imported inRusing theimportfunction, which will generate aGRangesobject.
fourDNData(experimentSetAccession = '4DNES25ABNZ1', type = 'boundaries') |>
import()
## GRanges object with 6103 ranges and 2 metadata columns:
## seqnames ranges strand | name score
## <Rle> <IRanges> <Rle> | <character> <numeric>
## [1] chr1 4380001-4385000 * | Strong 0.695274
## [2] chr1 4760001-4765000 * | Weak 0.444476
## [3] chr1 4910001-4915000 * | Weak 0.353184
## [4] chr1 5180001-5185000 * | Strong 0.565763
## [5] chr1 6170001-6175000 * | Strong 1.644911
## ... ... ... ... . ... ...
## [6099] chrY 89725001-89730000 * | Weak 0.258094
## [6100] chrY 89790001-89795000 * | Weak 0.442186
## [6101] chrY 89895001-89900000 * | Weak 0.279879
## [6102] chrY 90025001-90030000 * | Strong 0.660699
## [6103] chrY 90410001-90415000 * | Strong 1.160018
## -------
## seqinfo: 21 sequences from an unspecified genome; no seqlengths-
type = 'compartments'will fetch a.bigwigtrack file precomputed by the 4DN consortium. This track corresponds to the selected genome-wide eigenvector computed bycooltoolsand representing A/B compartments. To know more about this, read the excerpt from 4DN data portal. Once fetched from the 4DN data portal, the local file can be imported inRusing theimportfunction, which will generate aRleListobject. The score represents the eigenvector values, and by convention a genomic bin with a positive score is associated with the A compartment whereas a genomic bin with a negative score is associated with the B compartment.
fourDNData(experimentSetAccession = '4DNES25ABNZ1', type = 'compartments') |>
import()
## GRanges object with 10911 ranges and 1 metadata column:
## seqnames ranges strand | score
## <Rle> <IRanges> <Rle> | <numeric>
## [1] chr1 1-250000 * | NaN
## [2] chr1 250001-500000 * | NaN
## [3] chr1 500001-750000 * | NaN
## [4] chr1 750001-1000000 * | NaN
## [5] chr1 1000001-1250000 * | NaN
## ... ... ... ... . ...
## [10907] chrY 90500001-90750000 * | 0.0237907
## [10908] chrY 90750001-91000000 * | NaN
## [10909] chrY 91000001-91250000 * | NaN
## [10910] chrY 91250001-91500000 * | NaN
## [10911] chrY 91500001-91744698 * | NaN
## -------
## seqinfo: 21 sequences from an unspecified genome8.1.2 Querying a complete experiment dataset
Rather than importing multiple files corresponding to a single experimentSet accession ID one by one, one can import all the available files associated with a experimentSet accession ID into a HiCExperiment object by using the fourDNHiCExperiment() function.
hic <- fourDNHiCExperiment('4DNESJNPEKZD')
## Fetching local Hi-C contact map from Bioc cache
## Fetching compartments bigwig file from 4DN portal
## Insulation not found for the provided experimentSet accession.
## Borders not found for the provided experimentSet accession.
## Importing contacts in memoryThis is a more efficient way to import datasets, as it aggregates the different bits together into a single HiCExperiment object with populated topologicalFeatures and metadata slots.
hic
## `HiCExperiment` object with 453,301 contacts over 12,366 regions
## -------
## fileName: "/root/.cache/R/fourDNData/150e6c94d4df_4DNFIZL8OZE1.mcool"
## focus: "whole genome"
## resolutions(13): 1000 2000 ... 5000000 10000000
## active resolution: 250000
## interactions: 289086
## scores(2): count balanced
## topologicalFeatures: compartments(5437) borders(0)
## pairsFile: N/A
## metadata(2): 4DN_info eigensmetadata(hic)
## $`4DN_info`
## experimentSetAccession fileType size organism experimentType
## 1376 4DNESJNPEKZD pairs 6.67 human in situ Hi-C
## 1378 4DNESJNPEKZD hic 179.51 human in situ Hi-C
## 1379 4DNESJNPEKZD mcool 30.17 human in situ Hi-C
## 1380 4DNESJNPEKZD compartments 0.21 human in situ Hi-C
## details dataset
## 1376 MboI Hi-C on GM12878 cells - protocol variations
## 1378 MboI Hi-C on GM12878 cells - protocol variations
## 1379 MboI Hi-C on GM12878 cells - protocol variations
## 1380 MboI Hi-C on GM12878 cells - protocol variations
## condition biosource
## 1376 in situ Hi-C on GM12878 with MboI and bio-dUTP (Tri-Link) GM12878
## 1378 in situ Hi-C on GM12878 with MboI and bio-dUTP (Tri-Link) GM12878
## 1379 in situ Hi-C on GM12878 with MboI and bio-dUTP (Tri-Link) GM12878
## 1380 in situ Hi-C on GM12878 with MboI and bio-dUTP (Tri-Link) GM12878
## biosourceType publication
## 1376 immortalized cell line Rao SS et al. (2014)
## 1378 immortalized cell line Rao SS et al. (2014)
## 1379 immortalized cell line Rao SS et al. (2014)
## 1380 immortalized cell line Rao SS et al. (2014)
## URL
## 1376 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/0bdd4745-7203-49d0-adf6-291cef1a96b7/4DNFIOZ7D1OQ.pairs.gz
## 1378 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/1201682a-a223-482d-913d-3c3972b8eb65/4DNFIIRIHBR2.hic
## 1379 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/356fab42-5562-4cfd-a3f8-592aa060b992/4DNFIZL8OZE1.mcool
## 1380 https://4dn-open-data-public.s3.amazonaws.com/fourfront-webprod/wfoutput/333aabfd-b747-447c-b93a-8138f9488fad/4DNFIO9V5G93.bw
##
## $eigens
## GRanges object with 11280 ranges and 2 metadata columns:
## seqnames ranges strand | score eigen
## <Rle> <IRanges> <Rle> | <numeric> <numeric>
## [1] chr1 750001-1000000 * | 1.6911879 1.6911879
## [2] chr1 1000001-1250000 * | 0.0809129 0.0809129
## [3] chr1 1250001-1500000 * | 0.0690173 0.0690173
## [4] chr1 1500001-1750000 * | -0.1903324 -0.1903324
## [5] chr1 1750001-2000000 * | 0.3283633 0.3283633
## ... ... ... ... . ... ...
## [11276] chrX 154750001-155000000 * | -0.10909061 -0.10909061
## [11277] chrX 155000001-155250000 * | -1.39655280 -1.39655280
## [11278] chrX 155250001-155500000 * | 0.00264734 0.00264734
## [11279] chrX 155500001-155750000 * | -0.15279847 -0.15279847
## [11280] chrX 155750001-156000000 * | -1.41699576 -1.41699576
## -------
## seqinfo: 24 sequences from an unspecified genome8.2 DNA Zoo
The DNA Zoo Consortium is a collaborative group whose aim is to correct and refine genome assemblies across the tree of life using Hi-C approaches. As of 2023, they have performed Hi-C across more than 300 animal, plant and fungi species.
DNAZooData is a package giving programmatic access to these uniformly processed Hi-C contact files, as well as the refined genome assemblies.
The DNAZooData() function provides a gateway to DNA Zoo-hosted Hi-C files, fetching and caching relevant contact matrices in .hic format It returns a HicFile object, which can then be imported in memory using import().
library(DNAZooData)
head(DNAZooData())
## species readme
## 1 Acinonyx_jubatus Acinonyx_jubatus/README.json
## 2 Acropora_millepora Acropora_millepora/README.json
## 3 Addax_nasomaculatus Addax_nasomaculatus/README.json
## 4 Aedes_aegypti Aedes_aegypti/README.json
## 5 Aedes_aegypti__AaegL4 Aedes_aegypti__AaegL4/README.json
## 6 Aedes_aegypti__AaegL5.0 Aedes_aegypti__AaegL5.0/README.json
## readme_link
## 1 https://dnazoo.s3.wasabisys.com/Acinonyx_jubatus/README.json
## 2 https://dnazoo.s3.wasabisys.com/Acropora_millepora/README.json
## 3 https://dnazoo.s3.wasabisys.com/Addax_nasomaculatus/README.json
## 4 https://dnazoo.s3.wasabisys.com/Aedes_aegypti/README.json
## 5 https://dnazoo.s3.wasabisys.com/Aedes_aegypti__AaegL4/README.json
## 6 https://dnazoo.s3.wasabisys.com/Aedes_aegypti__AaegL5.0/README.json
## original_assembly new_assembly
## 1 aciJub1 aciJub1_HiC
## 2 amil_sf_1.1 amil_sf_1.1_HiC
## 3 ASM1959352v1 ASM1959352v1_HiC
## 4 AGWG.draft AaegL5.0
## 5 AaegL3 AaegL4
## 6 AGWG.draft AaegL5.0
## new_assembly_link
## 1 https://dnazoo.s3.wasabisys.com/Acinonyx_jubatus/aciJub1_HiC.fasta.gz
## 2 https://dnazoo.s3.wasabisys.com/Acropora_millepora/amil_sf_1.1_HiC.fasta.gz
## 3 https://dnazoo.s3.wasabisys.com/Addax_nasomaculatus/ASM1959352v1_HiC.fasta.gz
## 4 https://dnazoo.s3.wasabisys.com/Aedes_aegypti/AaegL5.0.fasta.gz
## 5 https://dnazoo.s3.wasabisys.com/Aedes_aegypti__AaegL4/AaegL4.fasta.gz
## 6 https://dnazoo.s3.wasabisys.com/Aedes_aegypti__AaegL5.0/AaegL5.0.fasta.gz
## new_assembly_link_status
## 1 200
## 2 200
## 3 200
## 4 404
## 5 200
## 6 200
## hic_link
## 1 https://dnazoo.s3.wasabisys.com/Acinonyx_jubatus/aciJub1.rawchrom.hic
## 2 https://dnazoo.s3.wasabisys.com/Acropora_millepora/amil_sf_1.1_HiC.hic
## 3 https://dnazoo.s3.wasabisys.com/Addax_nasomaculatus/ASM1959352v1_HiC.hic
## 4 <NA>
## 5 https://dnazoo.s3.wasabisys.com/Aedes_aegypti__AaegL4/AaegL4.hic
## 6 https://dnazoo.s3.wasabisys.com/Aedes_aegypti__AaegL5.0/AaegL5.0.hicFor example, we can directly fetch a Hi-C dataset generated from a tardigrade sample by specifying the right species argument.
hicfile <- DNAZooData(species = 'Hypsibius_dujardini')
## Fetching Hi-C data from DNAZoo
## Fetching Hi-C metadata from DNAZoo
hicfile
## HicFile object
## .hic file: /root/.cache/R/DNAZooData/150e1fb4f43a_nHd_3.1_HiC.hic
## resolution: 5000
## pairs file:
## metadata(6): organism draftAssembly ... credits assemblyURLHere again, the resulting HicFile is populated with metadata parsed from the DNA Zoo data portal.
metadata(hicfile)$organism
## $vernacular
## [1] "Tardigrade"
##
## $binomial
## [1] "Hypsibius dujardini"
##
## $funFact
## [1] "<i>Hypsibius dujardini</i> is a species of tardigrade, a tiny microscopic organism. They are also commonly called water bears. This species is found world-wide!"
##
## $extraInfo
## [1] "on BioKIDS website"
##
## $extraInfoLink
## [1] "http://www.biokids.umich.edu/critters/Hypsibius_dujardini/"
##
## $image
## [1] "https://static.wixstatic.com/media/2b9330_82db39c219f24b20a75cb38943aad1fb~mv2.jpg"
##
## $imageCredit
## [1] "By Willow Gabriel, Goldstein Lab - https://www.flickr.com/photos/waterbears/1614095719/ Template:Uploader Transferred from en.wikipedia to Commons., CC BY-SA 2.5, https://commons.wikimedia.org/w/index.php?curid=2261992"
##
## $isChromognomes
## [1] "FALSE"
##
## $taxonomy
## [1] "Species:202423-914154-914155-914158-155166-155362-710171-710179-710192-155390-155420"HiCFile metadata also points to a URL to directly fetch the genome assembly corrected by the DNA Zoo consortium.
metadata(hicfile)$assemblyURL
## [1] "https://dnazoo.s3.wasabisys.com/Hypsibius_dujardini/nHd_3.1_HiC.fasta.gz"Session info
Click to expand π
sessioninfo::session_info(include_base = TRUE)
## β Session info ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
## setting value
## version R Under development (unstable) (2024-01-17 r85813)
## os Ubuntu 22.04.3 LTS
## system x86_64, linux-gnu
## ui X11
## language (EN)
## collate C
## ctype en_US.UTF-8
## tz Etc/UTC
## date 2024-01-22
## pandoc 3.1.1 @ /usr/local/bin/ (via rmarkdown)
##
## β Packages ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
## package * version date (UTC) lib source
## abind 1.4-5 2016-07-21 [2] CRAN (R 4.4.0)
## base * 4.4.0 2024-01-18 [3] local
## Biobase * 2.63.0 2023-10-24 [2] Bioconductor
## BiocFileCache 2.11.1 2023-10-26 [2] Bioconductor
## BiocGenerics * 0.49.1 2023-11-01 [2] Bioconductor
## BiocIO 1.13.0 2023-10-24 [2] Bioconductor
## BiocParallel 1.37.0 2023-10-24 [2] Bioconductor
## Biostrings 2.71.1 2023-10-25 [2] Bioconductor
## bit 4.0.5 2022-11-15 [2] CRAN (R 4.4.0)
## bit64 4.0.5 2020-08-30 [2] CRAN (R 4.4.0)
## bitops 1.0-7 2021-04-24 [2] CRAN (R 4.4.0)
## blob 1.2.4 2023-03-17 [2] CRAN (R 4.4.0)
## cachem 1.0.8 2023-05-01 [2] CRAN (R 4.4.0)
## cli 3.6.2 2023-12-11 [2] CRAN (R 4.4.0)
## codetools 0.2-19 2023-02-01 [3] CRAN (R 4.4.0)
## colorspace 2.1-0 2023-01-23 [2] CRAN (R 4.4.0)
## compiler 4.4.0 2024-01-18 [3] local
## crayon 1.5.2 2022-09-29 [2] CRAN (R 4.4.0)
## curl 5.2.0 2023-12-08 [2] CRAN (R 4.4.0)
## datasets * 4.4.0 2024-01-18 [3] local
## DBI 1.2.1 2024-01-12 [2] CRAN (R 4.4.0)
## dbplyr 2.4.0 2023-10-26 [2] CRAN (R 4.4.0)
## DelayedArray 0.29.0 2023-10-24 [2] Bioconductor
## digest 0.6.34 2024-01-11 [2] CRAN (R 4.4.0)
## DNAZooData * 1.3.0 2023-10-31 [2] Bioconductor
## dplyr 1.1.4 2023-11-17 [2] CRAN (R 4.4.0)
## evaluate 0.23 2023-11-01 [2] CRAN (R 4.4.0)
## fansi 1.0.6 2023-12-08 [2] CRAN (R 4.4.0)
## fastmap 1.1.1 2023-02-24 [2] CRAN (R 4.4.0)
## filelock 1.0.3 2023-12-11 [2] CRAN (R 4.4.0)
## fourDNData * 1.3.0 2023-10-31 [2] Bioconductor
## generics 0.1.3 2022-07-05 [2] CRAN (R 4.4.0)
## GenomeInfoDb * 1.39.5 2024-01-01 [2] Bioconductor 3.19 (R 4.4.0)
## GenomeInfoDbData 1.2.11 2024-01-22 [2] Bioconductor
## GenomicAlignments 1.39.2 2024-01-16 [2] Bioconductor 3.19 (R 4.4.0)
## GenomicRanges * 1.55.1 2023-10-29 [2] Bioconductor
## ggplot2 * 3.4.4 2023-10-12 [2] CRAN (R 4.4.0)
## glue 1.7.0 2024-01-09 [2] CRAN (R 4.4.0)
## graphics * 4.4.0 2024-01-18 [3] local
## grDevices * 4.4.0 2024-01-18 [3] local
## grid 4.4.0 2024-01-18 [3] local
## gtable 0.3.4 2023-08-21 [2] CRAN (R 4.4.0)
## HiCExperiment * 1.3.0 2023-10-24 [2] Bioconductor
## htmltools 0.5.7 2023-11-03 [2] CRAN (R 4.4.0)
## htmlwidgets 1.6.4 2023-12-06 [2] CRAN (R 4.4.0)
## httr 1.4.7 2023-08-15 [2] CRAN (R 4.4.0)
## InteractionSet * 1.31.0 2023-10-24 [2] Bioconductor
## IRanges * 2.37.1 2024-01-19 [2] Bioconductor 3.19 (R 4.4.0)
## jsonlite 1.8.8 2023-12-04 [2] CRAN (R 4.4.0)
## knitr 1.45 2023-10-30 [2] CRAN (R 4.4.0)
## lattice 0.22-5 2023-10-24 [3] CRAN (R 4.4.0)
## lifecycle 1.0.4 2023-11-07 [2] CRAN (R 4.4.0)
## magrittr 2.0.3 2022-03-30 [2] CRAN (R 4.4.0)
## Matrix 1.6-5 2024-01-11 [3] CRAN (R 4.4.0)
## MatrixGenerics * 1.15.0 2023-10-24 [2] Bioconductor
## matrixStats * 1.2.0 2023-12-11 [2] CRAN (R 4.4.0)
## memoise 2.0.1 2021-11-26 [2] CRAN (R 4.4.0)
## methods * 4.4.0 2024-01-18 [3] local
## munsell 0.5.0 2018-06-12 [2] CRAN (R 4.4.0)
## parallel 4.4.0 2024-01-18 [3] local
## pillar 1.9.0 2023-03-22 [2] CRAN (R 4.4.0)
## pkgconfig 2.0.3 2019-09-22 [2] CRAN (R 4.4.0)
## purrr 1.0.2 2023-08-10 [2] CRAN (R 4.4.0)
## R6 2.5.1 2021-08-19 [2] CRAN (R 4.4.0)
## Rcpp 1.0.12 2024-01-09 [2] CRAN (R 4.4.0)
## RCurl 1.98-1.14 2024-01-09 [2] CRAN (R 4.4.0)
## restfulr 0.0.15 2022-06-16 [2] CRAN (R 4.4.0)
## rhdf5 2.47.2 2024-01-15 [2] Bioconductor 3.19 (R 4.4.0)
## rhdf5filters 1.15.1 2023-11-06 [2] Bioconductor
## Rhdf5lib 1.25.1 2023-12-11 [2] Bioconductor 3.19 (R 4.4.0)
## rjson 0.2.21 2022-01-09 [2] CRAN (R 4.4.0)
## rlang 1.1.3 2024-01-10 [2] CRAN (R 4.4.0)
## rmarkdown 2.25 2023-09-18 [2] CRAN (R 4.4.0)
## Rsamtools 2.19.3 2024-01-17 [2] Bioconductor 3.19 (R 4.4.0)
## RSQLite 2.3.5 2024-01-21 [2] CRAN (R 4.4.0)
## rtracklayer * 1.63.0 2024-01-22 [2] Github (lawremi/rtracklayer@86407bb)
## S4Arrays 1.3.2 2024-01-14 [2] Bioconductor 3.19 (R 4.4.0)
## S4Vectors * 0.41.3 2024-01-01 [2] Bioconductor 3.19 (R 4.4.0)
## scales 1.3.0 2023-11-28 [2] CRAN (R 4.4.0)
## sessioninfo 1.2.2 2021-12-06 [2] CRAN (R 4.4.0)
## SparseArray 1.3.3 2024-01-14 [2] Bioconductor 3.19 (R 4.4.0)
## stats * 4.4.0 2024-01-18 [3] local
## stats4 * 4.4.0 2024-01-18 [3] local
## strawr 0.0.91 2023-03-29 [2] CRAN (R 4.4.0)
## SummarizedExperiment * 1.33.2 2024-01-07 [2] Bioconductor 3.19 (R 4.4.0)
## tibble 3.2.1 2023-03-20 [2] CRAN (R 4.4.0)
## tidyselect 1.2.0 2022-10-10 [2] CRAN (R 4.4.0)
## tools 4.4.0 2024-01-18 [3] local
## tzdb 0.4.0 2023-05-12 [2] CRAN (R 4.4.0)
## utf8 1.2.4 2023-10-22 [2] CRAN (R 4.4.0)
## utils * 4.4.0 2024-01-18 [3] local
## vctrs 0.6.5 2023-12-01 [2] CRAN (R 4.4.0)
## vroom 1.6.5 2023-12-05 [2] CRAN (R 4.4.0)
## withr 3.0.0 2024-01-16 [2] CRAN (R 4.4.0)
## xfun 0.41 2023-11-01 [2] CRAN (R 4.4.0)
## XML 3.99-0.16.1 2024-01-22 [2] CRAN (R 4.4.0)
## XVector 0.43.1 2024-01-10 [2] Bioconductor 3.19 (R 4.4.0)
## yaml 2.3.8 2023-12-11 [2] CRAN (R 4.4.0)
## zlibbioc 1.49.0 2023-10-24 [2] Bioconductor
##
## [1] /tmp/Rtmpq5g2WV/Rinstb37571687
## [2] /usr/local/lib/R/site-library
## [3] /usr/local/lib/R/library
##
## βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββReferences
Crane, E., Bian, Q., McCord, R. P., Lajoie, B. R., Wheeler, B. S., Ralston, E. J., Uzawa, S., Dekker, J., & Meyer, B. J. (2015). Condensin-driven remodelling of x chromosome topology during dosage compensation. Nature, 523(7559), 240β244. https://doi.org/10.1038/nature14450