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 Under development (unstable) (2025-02-12 r87715)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.1 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_1.11.3 BiocStyle_2.35.0
##
## loaded via a namespace (and not attached):
## [1] RColorBrewer_1.1-3
## [2] jsonlite_1.8.9
## [3] magrittr_2.0.3
## [4] ggtangle_0.0.6
## [5] GenomicFeatures_1.59.1
## [6] farver_2.1.2
## [7] rmarkdown_2.29
## [8] fs_1.6.5
## [9] BiocIO_1.17.1
## [10] zlibbioc_1.53.0
## [11] ragg_1.3.3
## [12] vctrs_0.6.5
## [13] memoise_2.0.1
## [14] Rsamtools_2.23.1
## [15] RCurl_1.98-1.16
## [16] ggtree_3.15.0
## [17] htmltools_0.5.8.1
## [18] S4Arrays_1.7.3
## [19] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [20] plotrix_3.8-4
## [21] AnnotationHub_3.15.0
## [22] curl_6.2.0
## [23] SparseArray_1.7.5
## [24] gridGraphics_0.5-1
## [25] sass_0.4.9
## [26] KernSmooth_2.23-26
## [27] bslib_0.9.0
## [28] htmlwidgets_1.6.4
## [29] desc_1.4.3
## [30] plyr_1.8.9
## [31] plotly_4.10.4
## [32] impute_1.81.0
## [33] cachem_1.1.0
## [34] GenomicAlignments_1.43.0
## [35] igraph_2.1.4
## [36] downloadthis_0.4.1
## [37] lifecycle_1.0.4
## [38] pkgconfig_2.0.3
## [39] Matrix_1.7-2
## [40] R6_2.6.0
## [41] fastmap_1.2.0
## [42] GenomeInfoDbData_1.2.13
## [43] MatrixGenerics_1.19.1
## [44] digest_0.6.37
## [45] aplot_0.2.4
## [46] enrichplot_1.27.4
## [47] colorspace_2.1-1
## [48] patchwork_1.3.0
## [49] AnnotationDbi_1.69.0
## [50] S4Vectors_0.45.4
## [51] textshaping_1.0.0
## [52] GenomicRanges_1.59.1
## [53] RSQLite_2.3.9
## [54] filelock_1.0.3
## [55] httr_1.4.7
## [56] abind_1.4-8
## [57] compiler_4.5.0
## [58] bit64_4.6.0-1
## [59] BiocParallel_1.41.0
## [60] DBI_1.2.3
## [61] gplots_3.2.0
## [62] R.utils_2.12.3
## [63] ChIPseeker_1.43.0
## [64] rappdirs_0.3.3
## [65] DelayedArray_0.33.5
## [66] rjson_0.2.23
## [67] caTools_1.18.3
## [68] gtools_3.9.5
## [69] tools_4.5.0
## [70] ape_5.8-1
## [71] R.oo_1.27.0
## [72] glue_1.8.0
## [73] restfulr_0.0.15
## [74] nlme_3.1-167
## [75] GOSemSim_2.33.0
## [76] grid_4.5.0
## [77] gridBase_0.4-7
## [78] reshape2_1.4.4
## [79] fgsea_1.33.2
## [80] generics_0.1.3
## [81] BSgenome_1.75.1
## [82] gtable_0.3.6
## [83] tzdb_0.4.0
## [84] R.methodsS3_1.8.2
## [85] seqPattern_1.39.0
## [86] tidyr_1.3.1
## [87] hms_1.1.3
## [88] data.table_1.16.4
## [89] XVector_0.47.2
## [90] BiocGenerics_0.53.6
## [91] ggrepel_0.9.6
## [92] BiocVersion_3.21.1
## [93] pillar_1.10.1
## [94] stringr_1.5.1
## [95] yulab.utils_0.2.0
## [96] splines_4.5.0
## [97] dplyr_1.1.4
## [98] treeio_1.31.0
## [99] BiocFileCache_2.15.1
## [100] lattice_0.22-6
## [101] rtracklayer_1.67.0
## [102] bit_4.5.0.1
## [103] tidyselect_1.2.1
## [104] GO.db_3.20.0
## [105] Biostrings_2.75.3
## [106] knitr_1.49
## [107] bookdown_0.42
## [108] IRanges_2.41.3
## [109] SummarizedExperiment_1.37.0
## [110] stats4_4.5.0
## [111] xfun_0.50
## [112] Biobase_2.67.0
## [113] matrixStats_1.5.0
## [114] stringi_1.8.4
## [115] UCSC.utils_1.3.1
## [116] lazyeval_0.2.2
## [117] ggfun_0.1.8
## [118] yaml_2.3.10
## [119] boot_1.3-31
## [120] evaluate_1.0.3
## [121] codetools_0.2-20
## [122] tibble_3.2.1
## [123] qvalue_2.39.0
## [124] BiocManager_1.30.25
## [125] ggplotify_0.1.2
## [126] cli_3.6.4
## [127] systemfonts_1.2.1
## [128] munsell_0.5.1
## [129] jquerylib_0.1.4
## [130] Rcpp_1.0.14
## [131] GenomeInfoDb_1.43.4
## [132] dbplyr_2.5.0
## [133] png_0.1-8
## [134] XML_3.99-0.18
## [135] parallel_4.5.0
## [136] readr_2.1.5
## [137] pkgdown_2.1.1
## [138] ggplot2_3.5.1
## [139] blob_1.2.4
## [140] DOSE_4.1.0
## [141] bitops_1.0-9
## [142] viridisLite_0.4.2
## [143] tidytree_0.4.6
## [144] scales_1.3.0
## [145] genomation_1.39.0
## [146] purrr_1.0.4
## [147] crayon_1.5.3
## [148] rlang_1.1.5
## [149] cowplot_1.1.3
## [150] fastmatch_1.1-6
## [151] KEGGREST_1.47.0