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/1780c614d0404c_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) (2024-10-21 r87258)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.1 LTS
#>
#> Matrix products: default
#> BLAS: /home/biocbuild/bbs-3.21-bioc/R/lib/libRblas.so
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0
#>
#> 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_1.9.0 ExperimentHub_2.15.0 AnnotationHub_3.15.0
#> [4] BiocFileCache_2.15.0 dbplyr_2.5.0 BiocGenerics_0.53.1
#> [7] generics_0.1.3 BiocStyle_2.35.0
#>
#> loaded via a namespace (and not attached):
#> [1] KEGGREST_1.47.0 xfun_0.49 bslib_0.8.0
#> [4] Biobase_2.67.0 vctrs_0.6.5 tools_4.5.0
#> [7] stats4_4.5.0 curl_5.2.3 tibble_3.2.1
#> [10] fansi_1.0.6 AnnotationDbi_1.69.0 RSQLite_2.3.7
#> [13] blob_1.2.4 pkgconfig_2.0.3 S4Vectors_0.45.0
#> [16] lifecycle_1.0.4 GenomeInfoDbData_1.2.13 compiler_4.5.0
#> [19] Biostrings_2.75.0 GenomeInfoDb_1.43.0 htmltools_0.5.8.1
#> [22] sass_0.4.9 yaml_2.3.10 pillar_1.9.0
#> [25] crayon_1.5.3 jquerylib_0.1.4 cachem_1.1.0
#> [28] mime_0.12 tidyselect_1.2.1 digest_0.6.37
#> [31] dplyr_1.1.4 purrr_1.0.2 bookdown_0.41
#> [34] BiocVersion_3.21.1 fastmap_1.2.0 cli_3.6.3
#> [37] magrittr_2.0.3 utf8_1.2.4 withr_3.0.2
#> [40] filelock_1.0.3 UCSC.utils_1.3.0 rappdirs_0.3.3
#> [43] bit64_4.5.2 rmarkdown_2.29 XVector_0.47.0
#> [46] httr_1.4.7 bit_4.5.0 png_0.1-8
#> [49] memoise_2.0.1 evaluate_1.0.1 knitr_1.48
#> [52] IRanges_2.41.0 rlang_1.1.4 glue_1.8.0
#> [55] DBI_1.2.3 BiocManager_1.30.25 jsonlite_1.8.9
#> [58] R6_2.5.1 zlibbioc_1.53.0