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 4.6.0 (2026-04-24)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.4 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: Etc/UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] EpiCompare_1.16.0 BiocStyle_2.40.0
##
## loaded via a namespace (and not attached):
## [1] RColorBrewer_1.1-3
## [2] sys_3.4.3
## [3] jsonlite_2.0.0
## [4] tidydr_0.0.6
## [5] magrittr_2.0.5
## [6] ggtangle_0.1.2
## [7] GenomicFeatures_1.64.0
## [8] farver_2.1.2
## [9] rmarkdown_2.31
## [10] fs_2.1.0
## [11] BiocIO_1.22.0
## [12] vctrs_0.7.3
## [13] memoise_2.0.1
## [14] Rsamtools_2.28.0
## [15] RCurl_1.98-1.18
## [16] ggtree_4.2.0
## [17] htmltools_0.5.9
## [18] S4Arrays_1.12.0
## [19] TxDb.Hsapiens.UCSC.hg19.knownGene_3.22.1
## [20] plotrix_3.8-14
## [21] AnnotationHub_4.2.0
## [22] curl_7.1.0
## [23] SparseArray_1.12.0
## [24] gridGraphics_0.5-1
## [25] sass_0.4.10
## [26] KernSmooth_2.23-26
## [27] bslib_0.10.0
## [28] htmlwidgets_1.6.4
## [29] plyr_1.8.9
## [30] httr2_1.2.2
## [31] plotly_4.12.0
## [32] impute_1.86.0
## [33] cachem_1.1.0
## [34] buildtools_1.0.0
## [35] GenomicAlignments_1.48.0
## [36] igraph_2.3.0
## [37] downloadthis_0.5.0
## [38] lifecycle_1.0.5
## [39] pkgconfig_2.0.3
## [40] Matrix_1.7-5
## [41] R6_2.6.1
## [42] fastmap_1.2.0
## [43] MatrixGenerics_1.24.0
## [44] digest_0.6.39
## [45] aplot_0.2.9
## [46] enrichplot_1.32.0
## [47] ggnewscale_0.5.2
## [48] patchwork_1.3.2
## [49] AnnotationDbi_1.74.0
## [50] S4Vectors_0.50.0
## [51] GenomicRanges_1.64.0
## [52] RSQLite_2.4.6
## [53] filelock_1.0.3
## [54] polyclip_1.10-7
## [55] httr_1.4.8
## [56] abind_1.4-8
## [57] compiler_4.6.0
## [58] withr_3.0.2
## [59] bit64_4.8.0
## [60] fontquiver_0.2.1
## [61] S7_0.2.2
## [62] BiocParallel_1.46.0
## [63] DBI_1.3.0
## [64] gplots_3.3.0
## [65] ggforce_0.5.0
## [66] MASS_7.3-65
## [67] ChIPseeker_1.48.0
## [68] rappdirs_0.3.4
## [69] DelayedArray_0.38.0
## [70] rjson_0.2.23
## [71] caTools_1.18.3
## [72] gtools_3.9.5
## [73] tools_4.6.0
## [74] otel_0.2.0
## [75] scatterpie_0.2.6
## [76] ape_5.8-1
## [77] glue_1.8.1
## [78] restfulr_0.0.16
## [79] nlme_3.1-169
## [80] GOSemSim_2.38.0
## [81] grid_4.6.0
## [82] gridBase_0.4-7
## [83] cluster_2.1.8.2
## [84] reshape2_1.4.5
## [85] generics_0.1.4
## [86] BSgenome_1.80.0
## [87] gtable_0.3.6
## [88] tzdb_0.5.0
## [89] seqPattern_1.42.0
## [90] tidyr_1.3.2
## [91] hms_1.1.4
## [92] data.table_1.18.2.1
## [93] XVector_0.52.0
## [94] BiocGenerics_0.58.0
## [95] ggrepel_0.9.8
## [96] BiocVersion_3.23.1
## [97] pillar_1.11.1
## [98] stringr_1.6.0
## [99] yulab.utils_0.2.4
## [100] tweenr_2.0.3
## [101] dplyr_1.2.1
## [102] treeio_1.36.0
## [103] BiocFileCache_3.2.0
## [104] lattice_0.22-9
## [105] rtracklayer_1.72.0
## [106] bit_4.6.0
## [107] tidyselect_1.2.1
## [108] fontLiberation_0.1.0
## [109] GO.db_3.22.0
## [110] maketools_1.3.2
## [111] Biostrings_2.80.0
## [112] knitr_1.51
## [113] fontBitstreamVera_0.1.1
## [114] IRanges_2.46.0
## [115] Seqinfo_1.2.0
## [116] SummarizedExperiment_1.42.0
## [117] stats4_4.6.0
## [118] xfun_0.57
## [119] Biobase_2.72.0
## [120] matrixStats_1.5.0
## [121] stringi_1.8.7
## [122] UCSC.utils_1.8.0
## [123] lazyeval_0.2.3
## [124] ggfun_0.2.0
## [125] yaml_2.3.12
## [126] boot_1.3-32
## [127] evaluate_1.0.5
## [128] codetools_0.2-20
## [129] cigarillo_1.2.0
## [130] gdtools_0.5.0
## [131] tibble_3.3.1
## [132] BiocManager_1.30.27
## [133] ggplotify_0.1.3
## [134] cli_3.6.6
## [135] systemfonts_1.3.2
## [136] jquerylib_0.1.4
## [137] Rcpp_1.1.1-1.1
## [138] GenomeInfoDb_1.48.0
## [139] dbplyr_2.5.2
## [140] png_0.1-9
## [141] XML_3.99-0.23
## [142] parallel_4.6.0
## [143] readr_2.2.0
## [144] ggplot2_4.0.3
## [145] blob_1.3.0
## [146] DOSE_4.6.0
## [147] bitops_1.0-9
## [148] viridisLite_0.4.3
## [149] tidytree_0.4.7
## [150] ggiraph_0.9.6
## [151] enrichit_0.1.4
## [152] scales_1.4.0
## [153] genomation_1.44.0
## [154] purrr_1.2.2
## [155] crayon_1.5.3
## [156] rlang_1.2.0
## [157] KEGGREST_1.52.0