8  Data gateways: accessing public Hi-C data portals

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library(fourDNData)
library(DNAZooData)
library(rtracklayer)
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:

  • fourDNData
  • DNAZooData

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 (β€œin situ” or β€œdilution” Hi-C, Capture Hi-C, Micro-C, DNase Hi-C, …), 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.bw

8.1.1 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] "/home/biocbuild/.cache/R/fourDNData/18eeaa3f86773e_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: "/home/biocbuild/.cache/R/fourDNData/18eeaa3f86773e_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 in R using the import function, which will generate a GInteractions object.
## 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 .bigwig track file precomputed by the 4DN consortium. This track corresponds to the genome-wide insulation score computed by cooltools as 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 in R using the import function, which will generate a RleList object.
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 .bed file 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 in R using the import function, which will generate a GRanges object.
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 .bigwig track file precomputed by the 4DN consortium. This track corresponds to the selected genome-wide eigenvector computed by cooltools and 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 in R using the import function, which will generate a RleList object. 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 genome

8.1.2 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 local compartments bigwig file from Bioc cache
##  Insulation not found for the provided experimentSet accession.
##  Borders not found for the provided experimentSet accession.
##  Importing contacts in memory

This 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: "/home/biocbuild/.cache/R/fourDNData/18eeaa3f86773e_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 eigens
metadata(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 genome

8.2 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.hic

For 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')

hicfile
##  HicFile object
##  .hic file: /home/biocbuild/.cache/R/DNAZooData/18eeaa2cf5ff0d_nHd_3.1_HiC.hic 
##  resolution: 5000 
##  pairs file: 
##  metadata(6): organism draftAssembly ... credits assemblyURL

Here 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

sessioninfo::session_info(include_base = TRUE)
##  ─ Session info ────────────────────────────────────────────────────────────
##   setting  value
##   version  R version 4.4.1 (2024-06-14)
##   os       Ubuntu 24.04.1 LTS
##   system   x86_64, linux-gnu
##   ui       X11
##   language (EN)
##   collate  C
##   ctype    en_US.UTF-8
##   tz       America/New_York
##   date     2024-10-30
##   pandoc   2.7.3 @ /usr/bin/ (via rmarkdown)
##  
##  ─ Packages ────────────────────────────────────────────────────────────────
##   package              * version   date (UTC) lib source
##   abind                  1.4-8     2024-09-12 [2] CRAN (R 4.4.1)
##   base                 * 4.4.1     2024-09-25 [3] local
##   Biobase              * 2.66.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   BiocFileCache          2.14.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   BiocGenerics         * 0.52.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   BiocIO                 1.16.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   BiocParallel           1.40.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   Biostrings             2.74.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   bit                    4.5.0     2024-09-20 [2] CRAN (R 4.4.1)
##   bit64                  4.5.2     2024-09-22 [2] CRAN (R 4.4.1)
##   bitops                 1.0-9     2024-10-03 [2] CRAN (R 4.4.1)
##   blob                   1.2.4     2023-03-17 [2] CRAN (R 4.4.1)
##   cachem                 1.1.0     2024-05-16 [2] CRAN (R 4.4.1)
##   cli                    3.6.3     2024-06-21 [2] CRAN (R 4.4.1)
##   codetools              0.2-20    2024-03-31 [3] CRAN (R 4.4.1)
##   colorspace             2.1-1     2024-07-26 [2] CRAN (R 4.4.1)
##   compiler               4.4.1     2024-09-25 [3] local
##   crayon                 1.5.3     2024-06-20 [2] CRAN (R 4.4.1)
##   curl                   5.2.3     2024-09-20 [2] CRAN (R 4.4.1)
##   datasets             * 4.4.1     2024-09-25 [3] local
##   DBI                    1.2.3     2024-06-02 [2] CRAN (R 4.4.1)
##   dbplyr                 2.5.0     2024-03-19 [2] CRAN (R 4.4.1)
##   DelayedArray           0.32.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   digest                 0.6.37    2024-08-19 [2] CRAN (R 4.4.1)
##   DNAZooData           * 1.5.0     2024-10-26 [2] Bioconductor 3.20 (R 4.4.1)
##   dplyr                  1.1.4     2023-11-17 [2] CRAN (R 4.4.1)
##   evaluate               1.0.1     2024-10-10 [2] CRAN (R 4.4.1)
##   fansi                  1.0.6     2023-12-08 [2] CRAN (R 4.4.1)
##   fastmap                1.2.0     2024-05-15 [2] CRAN (R 4.4.1)
##   filelock               1.0.3     2023-12-11 [2] CRAN (R 4.4.1)
##   fourDNData           * 1.5.0     2024-10-26 [2] Bioconductor 3.20 (R 4.4.1)
##   generics               0.1.3     2022-07-05 [2] CRAN (R 4.4.1)
##   GenomeInfoDb         * 1.42.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   GenomeInfoDbData       1.2.13    2024-10-01 [2] Bioconductor
##   GenomicAlignments      1.42.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   GenomicRanges        * 1.58.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   ggplot2              * 3.5.1     2024-04-23 [2] CRAN (R 4.4.1)
##   glue                   1.8.0     2024-09-30 [2] CRAN (R 4.4.1)
##   graphics             * 4.4.1     2024-09-25 [3] local
##   grDevices            * 4.4.1     2024-09-25 [3] local
##   grid                   4.4.1     2024-09-25 [3] local
##   gtable                 0.3.6     2024-10-25 [2] CRAN (R 4.4.1)
##   HiCExperiment        * 1.6.0     2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   htmltools              0.5.8.1   2024-04-04 [2] CRAN (R 4.4.1)
##   htmlwidgets            1.6.4     2023-12-06 [2] CRAN (R 4.4.1)
##   httr                   1.4.7     2023-08-15 [2] CRAN (R 4.4.1)
##   InteractionSet       * 1.34.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   IRanges              * 2.40.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   jsonlite               1.8.9     2024-09-20 [2] CRAN (R 4.4.1)
##   knitr                  1.48      2024-07-07 [2] CRAN (R 4.4.1)
##   lattice                0.22-6    2024-03-20 [3] CRAN (R 4.4.1)
##   lifecycle              1.0.4     2023-11-07 [2] CRAN (R 4.4.1)
##   magrittr               2.0.3     2022-03-30 [2] CRAN (R 4.4.1)
##   Matrix                 1.7-1     2024-10-18 [3] CRAN (R 4.4.1)
##   MatrixGenerics       * 1.18.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   matrixStats          * 1.4.1     2024-09-08 [2] CRAN (R 4.4.1)
##   memoise                2.0.1     2021-11-26 [2] CRAN (R 4.4.1)
##   methods              * 4.4.1     2024-09-25 [3] local
##   munsell                0.5.1     2024-04-01 [2] CRAN (R 4.4.1)
##   parallel               4.4.1     2024-09-25 [3] local
##   pillar                 1.9.0     2023-03-22 [2] CRAN (R 4.4.1)
##   pkgconfig              2.0.3     2019-09-22 [2] CRAN (R 4.4.1)
##   purrr                  1.0.2     2023-08-10 [2] CRAN (R 4.4.1)
##   R6                     2.5.1     2021-08-19 [2] CRAN (R 4.4.1)
##   Rcpp                   1.0.13    2024-07-17 [2] CRAN (R 4.4.1)
##   RCurl                  1.98-1.16 2024-07-11 [2] CRAN (R 4.4.1)
##   restfulr               0.0.15    2022-06-16 [2] CRAN (R 4.4.1)
##   rhdf5                  2.50.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   rhdf5filters           1.18.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   Rhdf5lib               1.28.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   rjson                  0.2.23    2024-09-16 [2] CRAN (R 4.4.1)
##   rlang                  1.1.4     2024-06-04 [2] CRAN (R 4.4.1)
##   rmarkdown              2.28      2024-08-17 [2] CRAN (R 4.4.1)
##   Rsamtools              2.22.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   RSQLite                2.3.7     2024-05-27 [2] CRAN (R 4.4.1)
##   rtracklayer          * 1.66.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   S4Arrays               1.6.0     2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   S4Vectors            * 0.44.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   scales                 1.3.0     2023-11-28 [2] CRAN (R 4.4.1)
##   sessioninfo            1.2.2     2021-12-06 [2] CRAN (R 4.4.1)
##   SparseArray            1.6.0     2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   stats                * 4.4.1     2024-09-25 [3] local
##   stats4               * 4.4.1     2024-09-25 [3] local
##   strawr                 0.0.92    2024-07-16 [2] CRAN (R 4.4.1)
##   SummarizedExperiment * 1.36.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   tibble                 3.2.1     2023-03-20 [2] CRAN (R 4.4.1)
##   tidyselect             1.2.1     2024-03-11 [2] CRAN (R 4.4.1)
##   tools                  4.4.1     2024-09-25 [3] local
##   tzdb                   0.4.0     2023-05-12 [2] CRAN (R 4.4.1)
##   UCSC.utils             1.2.0     2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   utf8                   1.2.4     2023-10-22 [2] CRAN (R 4.4.1)
##   utils                * 4.4.1     2024-09-25 [3] local
##   vctrs                  0.6.5     2023-12-01 [2] CRAN (R 4.4.1)
##   vroom                  1.6.5     2023-12-05 [2] CRAN (R 4.4.1)
##   withr                  3.0.2     2024-10-28 [2] CRAN (R 4.4.1)
##   xfun                   0.48      2024-10-03 [2] CRAN (R 4.4.1)
##   XML                    3.99-0.17 2024-06-25 [2] CRAN (R 4.4.1)
##   XVector                0.46.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##   yaml                   2.3.10    2024-07-26 [2] CRAN (R 4.4.1)
##   zlibbioc               1.52.0    2024-10-29 [2] Bioconductor 3.20 (R 4.4.1)
##  
##   [1] /home/biocbuild/bbs-3.20-books/tmpdir/RtmphzOvfD/Rinst2020235c565b68
##   [2] /home/biocbuild/bbs-3.20-bioc/R/site-library
##   [3] /home/biocbuild/bbs-3.20-bioc/R/library
##  
##  ───────────────────────────────────────────────────────────────────────────

References

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), 240–244. https://doi.org/10.1038/nature14450
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