epicompare 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.
## R version 4.6.1 (2026-06-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 26.04.1 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-r0.3.32.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: Etc/UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] EpiCompare_1.17.0 BiocStyle_2.41.0
##
## loaded via a namespace (and not attached):
## [1] RColorBrewer_1.1-3
## [2] sys_3.4.3
## [3] jsonlite_2.0.0
## [4] tidydr_0.0.7
## [5] magrittr_2.0.5
## [6] ggtangle_0.1.3
## [7] GenomicFeatures_1.65.0
## [8] farver_2.1.2
## [9] rmarkdown_2.32
## [10] fs_2.1.0
## [11] BiocIO_1.23.3
## [12] vctrs_0.7.3
## [13] memoise_2.0.1
## [14] Rsamtools_2.29.0
## [15] RCurl_1.98-1.20
## [16] ggtree_4.3.0
## [17] htmltools_0.5.9
## [18] TxDb.Hsapiens.UCSC.hg19.knownGene_3.22.1
## [19] BiocBaseUtils_1.15.1
## [20] plotrix_3.8-14
## [21] AnnotationHub_4.3.2
## [22] curl_8.0.0
## [23] gridGraphics_0.5-1
## [24] sass_0.4.10
## [25] KernSmooth_2.23-27
## [26] bslib_0.12.0
## [27] htmlwidgets_1.6.4
## [28] plyr_1.8.9
## [29] httr2_1.3.0
## [30] plotly_4.12.1
## [31] impute_1.87.0
## [32] cachem_1.1.0
## [33] buildtools_1.0.0
## [34] GenomicAlignments_1.49.2
## [35] igraph_2.3.4
## [36] downloadthis_0.5.0
## [37] lifecycle_1.0.5
## [38] pkgconfig_2.0.3
## [39] Matrix_1.7-6
## [40] R6_2.6.1
## [41] fastmap_1.2.0
## [42] digest_0.6.39
## [43] aplot_0.3.2
## [44] enrichplot_1.99.8
## [45] ggnewscale_0.5.2
## [46] patchwork_1.3.2
## [47] AnnotationDbi_1.75.2
## [48] S4Vectors_0.51.10
## [49] GenomicRanges_1.65.4
## [50] RSQLite_3.53.3
## [51] filelock_1.0.3
## [52] httr_1.4.9
## [53] polyclip_1.10-7
## [54] compiler_4.6.1
## [55] withr_3.0.3
## [56] bit64_4.8.6
## [57] fontquiver_0.2.1
## [58] S7_0.2.2
## [59] BiocParallel_1.47.0
## [60] DBI_1.3.0
## [61] gplots_3.3.0
## [62] ggforce_0.5.0
## [63] MASS_7.3-66
## [64] ChIPseeker_1.49.3
## [65] rappdirs_0.3.4
## [66] rjson_0.2.23
## [67] caTools_1.18.4
## [68] gtools_3.9.5
## [69] tools_4.6.1
## [70] otel_0.2.0
## [71] ape_5.8-1
## [72] scatterpie_0.2.6
## [73] glue_1.8.1
## [74] restfulr_0.0.17
## [75] nlme_3.1-171
## [76] GOSemSim_2.39.4
## [77] grid_4.6.1
## [78] gridBase_0.4-7
## [79] cluster_2.1.8.3
## [80] reshape2_1.4.5
## [81] generics_0.1.4
## [82] BSgenome_1.81.1
## [83] gtable_0.3.6
## [84] tzdb_0.5.0
## [85] seqPattern_1.45.0
## [86] tidyr_1.3.2
## [87] hms_1.1.4
## [88] data.table_1.18.6.1
## [89] XVector_0.53.0
## [90] BiocGenerics_0.59.12
## [91] ggrepel_0.9.8
## [92] BiocVersion_3.24.0
## [93] pillar_1.11.1
## [94] stringr_1.6.0
## [95] yulab.utils_0.2.5
## [96] dplyr_1.2.1
## [97] tweenr_2.0.3
## [98] BiocFileCache_3.3.0
## [99] treeio_1.37.1
## [100] lattice_0.23-1
## [101] rtracklayer_1.73.0
## [102] bit_4.6.0
## [103] tidyselect_1.2.1
## [104] fontLiberation_0.1.0
## [105] GO.db_3.23.1
## [106] maketools_1.3.2
## [107] Biostrings_2.81.9
## [108] knitr_1.52
## [109] fontBitstreamVera_0.1.1
## [110] IRanges_2.47.5
## [111] Seqinfo_1.3.2
## [112] stats4_4.6.1
## [113] xfun_0.61
## [114] Biobase_2.73.2
## [115] matrixStats_1.5.0
## [116] stringi_1.8.9
## [117] UCSC.utils_1.9.0
## [118] lazyeval_0.2.3
## [119] ggfun_0.2.2
## [120] yaml_2.3.12
## [121] boot_1.3-32
## [122] evaluate_1.0.5
## [123] codetools_0.2-20
## [124] cigarillo_1.3.1
## [125] gdtools_0.5.1
## [126] tibble_3.3.1
## [127] BiocManager_1.30.27
## [128] ggplotify_0.1.3
## [129] cli_3.6.6
## [130] systemfonts_1.3.2
## [131] jquerylib_0.1.4
## [132] Rcpp_1.1.2
## [133] GenomeInfoDb_1.49.1
## [134] dbplyr_2.6.0
## [135] png_0.1-9
## [136] XML_3.99-0.25
## [137] parallel_4.6.1
## [138] readr_2.2.0
## [139] ggplot2_4.0.3
## [140] blob_1.3.0
## [141] DOSE_4.7.3
## [142] bitops_1.1-0
## [143] viridisLite_0.4.3
## [144] tidytree_0.4.8
## [145] ggiraph_0.9.6
## [146] enrichit_0.2.6
## [147] scales_1.4.0
## [148] genomation_1.45.0
## [149] purrr_1.2.2
## [150] crayon_1.5.3
## [151] rlang_1.3.0
## [152] KEGGREST_1.53.6