HiContactsData is a companion data package giving programmatic access to
several processed Hi-C files for demonstration, such as cool, mcool and
pairs files. It is meant to be used with HiContacts
.
library(HiContactsData)
The only function provided by HiContactsData package is HiContactsData()
.
Several files are available using this function, namely:
sample
: yeast_wt
, format
= fastq_R{12}
)sample
: yeast_wt
, format
= HiCool_log
)sample
: yeast_wt
, format
= cool
)sample
: yeast_wt
, format
= mcool
)sample
: yeast_g1
, format
= mcool
)sample
: yeast_g1
, format
= mcool
)sample
: yeast_g2m
, format
= pairs
)sample
: yeast_g2m
, format
= pairs
)sample
: yeast_wt
, format
= hic
)sample
: yeast_wt
, format
= hicpro_matrix
)sample
: yeast_wt
, format
= hicpro_bed
)sample
: yeast_wt
, format
= pairs
)sample
: yeast_Eco1
, format
= mcool
)sample
: yeast_Eco1
, format
= pairs
)sample
: mESCs
, format
= mcool
)sample
: mESCs
, format
= pairs
)sample
: microC
, format
= mcool
)Yeast data comes from Bastie, Chapard et al., Nature Structural & Molecular Biology 2022 and mouse ESC data comes from Bonev et al., Cell 2017. Human HcFF6 micro-C data comes from Krietenstein et al., Mol. Cell 2020.
To download one of these files, one can specify a sample
and a file format
:
cool_file <- HiContactsData()
#> Available files:
#> sample format genome condition
#> 1 yeast_wt fastq_R1 S288C wild-type
#> 2 yeast_wt fastq_R2 S288C wild-type
#> 3 yeast_wt HiCool_log S288C wild-type
#> 4 yeast_wt pairs.gz S288C wild-type
#> 5 yeast_wt cool S288C wild-type
#> 6 yeast_wt mcool S288C wild-type
#> 7 yeast_g1 mcool S288C wild-type
#> 8 yeast_g1 pairs S288C wild-type
#> 9 yeast_g2m mcool S288C wild-type
#> 10 yeast_g2m pairs S288C wild-type
#> 11 yeast_wt hic S288C wild-type
#> 12 yeast_wt hicpro_matrix S288C wild-type
#> 13 yeast_wt hicpro_bed S288C wild-type
#> 14 yeast_wt hicpro_pairs S288C wild-type
#> 15 yeast_eco1 mcool S288C Eco1-AID+IAA
#> 16 yeast_eco1 pairs.gz S288C Eco1-AID+IAA
#> 17 mESCs mcool mm10 mESCs
#> 18 mESCs pairs.gz mm10 mESCs
#> 19 microC mcool GRCh38 HFFc6
#> notes EHID
#> 1 fastq (R1) EH7783
#> 2 fastq (R2) EH7784
#> 3 HiCool log file EH7785
#> 4 only pairs from chrII are provided EH7703
#> 5 .cool file @ resolution of 1kb EH7701
#> 6 multi-res .mcool file EH7702
#> 7 multi-res .mcool file EH8562
#> 8 filtered pairs are provided EH8564
#> 9 multi-res .mcool file EH8563
#> 10 filtered pairs are provided EH8565
#> 11 multi-res .hic file EH7786
#> 12 HiC-Pro matrix file @ 1kb EH7787
#> 13 HiC-Pro bed file @ 1kb EH7788
#> 14 HiC-Pro .allValidPairs file EH7789
#> 15 multi-res .mcool file EH7704
#> 16 only pairs from chrII are provided EH7705
#> 17 multi-res .mcool file EH7706
#> 18 only pairs from chr13 are provided EH7707
#> 19 multi-res .mcool file, only chr17 is provided EH8535
#>
cool_file <- HiContactsData(sample = 'yeast_wt', format = 'cool')
#> see ?HiContactsData and browseVignettes('HiContactsData') for documentation
#> loading from cache
cool_file
#> EH7701
#> "/home/biocbuild/.cache/R/ExperimentHub/2dea606181df1b_7751"
HiCExperiment
package can be used to import data provided by HiContactsData
.
Refer to HiCExperiment
package documentation for further information.
sessionInfo()
#> R Under development (unstable) (2024-01-16 r85808)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 22.04.3 LTS
#>
#> Matrix products: default
#> BLAS: /home/biocbuild/bbs-3.19-bioc/R/lib/libRblas.so
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_GB LC_COLLATE=C
#> [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
#> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
#> [9] LC_ADDRESS=C LC_TELEPHONE=C
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: America/New_York
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] HiContactsData_1.5.3 ExperimentHub_2.11.1 AnnotationHub_3.11.1
#> [4] BiocFileCache_2.11.1 dbplyr_2.4.0 BiocGenerics_0.49.1
#> [7] BiocStyle_2.31.0
#>
#> loaded via a namespace (and not attached):
#> [1] KEGGREST_1.43.0 xfun_0.41 bslib_0.6.1
#> [4] Biobase_2.63.0 vctrs_0.6.5 tools_4.4.0
#> [7] bitops_1.0-7 generics_0.1.3 stats4_4.4.0
#> [10] curl_5.2.0 tibble_3.2.1 fansi_1.0.6
#> [13] AnnotationDbi_1.65.2 RSQLite_2.3.5 blob_1.2.4
#> [16] pkgconfig_2.0.3 S4Vectors_0.41.3 lifecycle_1.0.4
#> [19] GenomeInfoDbData_1.2.11 compiler_4.4.0 Biostrings_2.71.1
#> [22] GenomeInfoDb_1.39.5 htmltools_0.5.7 sass_0.4.8
#> [25] RCurl_1.98-1.14 yaml_2.3.8 pillar_1.9.0
#> [28] crayon_1.5.2 jquerylib_0.1.4 cachem_1.0.8
#> [31] mime_0.12 tidyselect_1.2.0 digest_0.6.34
#> [34] dplyr_1.1.4 purrr_1.0.2 bookdown_0.37
#> [37] BiocVersion_3.19.1 fastmap_1.1.1 cli_3.6.2
#> [40] magrittr_2.0.3 utf8_1.2.4 withr_3.0.0
#> [43] filelock_1.0.3 rappdirs_0.3.3 bit64_4.0.5
#> [46] rmarkdown_2.25 XVector_0.43.1 httr_1.4.7
#> [49] bit_4.0.5 png_0.1-8 memoise_2.0.1
#> [52] evaluate_0.23 knitr_1.45 IRanges_2.37.1
#> [55] rlang_1.1.3 glue_1.7.0 DBI_1.2.1
#> [58] BiocManager_1.30.22 jsonlite_1.8.8 R6_2.5.1
#> [61] zlibbioc_1.49.0