vignettes/docker.Rmd
docker.Rmdepicompare is now available via DockerHub as a containerised environment with Rstudio and all necessary dependencies pre-installed.
First, install Docker if you have not already.
Create an image of the Docker container in command line:
docker pull neurogenomicslab/epicompareOnce the image has been created, you can launch it with:
docker run \
-d \
-e ROOT=true \
-e PASSWORD="<your_password>" \
-v ~/Desktop:/Desktop \
-v /Volumes:/Volumes \
-p 8787:8787 \
neurogenomicslab/epicompare<your_password> above with
whatever you want your password to be.-v flags for your
particular use case.-d ensures the container will run in “detached”
mode, which means it will persist even after you’ve closed your command
line session.If you are using a system that does not allow Docker (as is the case for many institutional computing clusters), you can instead install Docker images via Singularity.
singularity pull docker://neurogenomicslab/epicompareFinally, launch the containerised Rstudio by entering the following URL in any web browser: http://localhost:8787/
Login using the credentials set during the Installation steps.
utils::sessionInfo()## R version 4.5.1 (2025-06-13)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.3 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so; LAPACK version 3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [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: UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] EpiCompare_1.12.2 BiocStyle_2.36.0
##
## loaded via a namespace (and not attached):
## [1] RColorBrewer_1.1-3
## [2] jsonlite_2.0.0
## [3] magrittr_2.0.4
## [4] ggtangle_0.0.7
## [5] GenomicFeatures_1.60.0
## [6] farver_2.1.2
## [7] rmarkdown_2.30
## [8] fs_1.6.6
## [9] BiocIO_1.18.0
## [10] ragg_1.5.0
## [11] vctrs_0.6.5
## [12] memoise_2.0.1
## [13] Rsamtools_2.24.1
## [14] RCurl_1.98-1.17
## [15] ggtree_3.16.3
## [16] htmltools_0.5.8.1
## [17] S4Arrays_1.8.1
## [18] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [19] plotrix_3.8-4
## [20] AnnotationHub_3.16.1
## [21] curl_7.0.0
## [22] SparseArray_1.8.1
## [23] gridGraphics_0.5-1
## [24] sass_0.4.10
## [25] KernSmooth_2.23-26
## [26] bslib_0.9.0
## [27] htmlwidgets_1.6.4
## [28] desc_1.4.3
## [29] plyr_1.8.9
## [30] plotly_4.11.0
## [31] impute_1.82.0
## [32] cachem_1.1.0
## [33] GenomicAlignments_1.44.0
## [34] igraph_2.1.4
## [35] downloadthis_0.5.0
## [36] lifecycle_1.0.4
## [37] pkgconfig_2.0.3
## [38] Matrix_1.7-4
## [39] R6_2.6.1
## [40] fastmap_1.2.0
## [41] GenomeInfoDbData_1.2.14
## [42] MatrixGenerics_1.20.0
## [43] digest_0.6.37
## [44] aplot_0.2.9
## [45] enrichplot_1.28.4
## [46] patchwork_1.3.2
## [47] AnnotationDbi_1.70.0
## [48] S4Vectors_0.46.0
## [49] textshaping_1.0.3
## [50] GenomicRanges_1.60.0
## [51] RSQLite_2.4.3
## [52] filelock_1.0.3
## [53] httr_1.4.7
## [54] abind_1.4-8
## [55] compiler_4.5.1
## [56] bit64_4.6.0-1
## [57] S7_0.2.0
## [58] BiocParallel_1.42.2
## [59] DBI_1.2.3
## [60] gplots_3.2.0
## [61] R.utils_2.13.0
## [62] ChIPseeker_1.44.0
## [63] rappdirs_0.3.3
## [64] DelayedArray_0.34.1
## [65] rjson_0.2.23
## [66] caTools_1.18.3
## [67] gtools_3.9.5
## [68] tools_4.5.1
## [69] ape_5.8-1
## [70] R.oo_1.27.1
## [71] glue_1.8.0
## [72] restfulr_0.0.16
## [73] nlme_3.1-168
## [74] GOSemSim_2.34.0
## [75] grid_4.5.1
## [76] gridBase_0.4-7
## [77] reshape2_1.4.4
## [78] fgsea_1.34.2
## [79] generics_0.1.4
## [80] BSgenome_1.76.0
## [81] gtable_0.3.6
## [82] tzdb_0.5.0
## [83] R.methodsS3_1.8.2
## [84] seqPattern_1.40.0
## [85] tidyr_1.3.1
## [86] hms_1.1.3
## [87] data.table_1.17.8
## [88] XVector_0.48.0
## [89] BiocGenerics_0.54.0
## [90] ggrepel_0.9.6
## [91] BiocVersion_3.21.1
## [92] pillar_1.11.1
## [93] stringr_1.5.2
## [94] yulab.utils_0.2.1
## [95] splines_4.5.1
## [96] dplyr_1.1.4
## [97] treeio_1.32.0
## [98] BiocFileCache_2.16.2
## [99] lattice_0.22-7
## [100] rtracklayer_1.68.0
## [101] bit_4.6.0
## [102] tidyselect_1.2.1
## [103] GO.db_3.21.0
## [104] Biostrings_2.76.0
## [105] knitr_1.50
## [106] bookdown_0.44
## [107] IRanges_2.42.0
## [108] SummarizedExperiment_1.38.1
## [109] stats4_4.5.1
## [110] xfun_0.53
## [111] Biobase_2.68.0
## [112] matrixStats_1.5.0
## [113] stringi_1.8.7
## [114] UCSC.utils_1.4.0
## [115] lazyeval_0.2.2
## [116] ggfun_0.2.0
## [117] yaml_2.3.10
## [118] boot_1.3-32
## [119] evaluate_1.0.5
## [120] codetools_0.2-20
## [121] tibble_3.3.0
## [122] qvalue_2.40.0
## [123] BiocManager_1.30.26
## [124] ggplotify_0.1.3
## [125] cli_3.6.5
## [126] systemfonts_1.2.3
## [127] jquerylib_0.1.4
## [128] Rcpp_1.1.0
## [129] GenomeInfoDb_1.44.3
## [130] dbplyr_2.5.1
## [131] png_0.1-8
## [132] XML_3.99-0.19
## [133] parallel_4.5.1
## [134] readr_2.1.5
## [135] pkgdown_2.1.3
## [136] ggplot2_4.0.0
## [137] blob_1.2.4
## [138] DOSE_4.2.0
## [139] bitops_1.0-9
## [140] viridisLite_0.4.2
## [141] tidytree_0.4.6
## [142] scales_1.4.0
## [143] genomation_1.40.1
## [144] purrr_1.1.0
## [145] crayon_1.5.3
## [146] rlang_1.1.6
## [147] cowplot_1.2.0
## [148] fastmatch_1.1-6
## [149] KEGGREST_1.48.1