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_1.17.0 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_0.0.6
## [5] magrittr_2.0.5
## [6] ggtangle_0.1.2
## [7] GenomicFeatures_1.65.0
## [8] farver_2.1.2
## [9] rmarkdown_2.31
## [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_1.98-1.18
## [16] ggtree_4.3.0
## [17] htmltools_0.5.9
## [18] S4Arrays_1.13.0
## [19] TxDb.Hsapiens.UCSC.hg19.knownGene_3.22.1
## [20] BiocBaseUtils_1.15.1
## [21] plotrix_3.8-14
## [22] AnnotationHub_4.3.0
## [23] curl_7.1.0
## [24] SparseArray_1.13.2
## [25] gridGraphics_0.5-1
## [26] sass_0.4.10
## [27] KernSmooth_2.23-26
## [28] bslib_0.11.0
## [29] htmlwidgets_1.6.4
## [30] plyr_1.8.9
## [31] httr2_1.2.2
## [32] plotly_4.12.0
## [33] impute_1.87.0
## [34] cachem_1.1.0
## [35] buildtools_1.0.0
## [36] GenomicAlignments_1.49.0
## [37] igraph_2.3.1
## [38] downloadthis_0.5.0
## [39] lifecycle_1.0.5
## [40] pkgconfig_2.0.3
## [41] Matrix_1.7-5
## [42] R6_2.6.1
## [43] fastmap_1.2.0
## [44] MatrixGenerics_1.25.0
## [45] digest_0.6.39
## [46] aplot_0.2.9
## [47] enrichplot_1.33.0
## [48] ggnewscale_0.5.2
## [49] patchwork_1.3.2
## [50] AnnotationDbi_1.75.0
## [51] S4Vectors_0.51.3
## [52] GenomicRanges_1.65.0
## [53] RSQLite_3.53.1
## [54] filelock_1.0.3
## [55] polyclip_1.10-7
## [56] httr_1.4.8
## [57] abind_1.4-8
## [58] compiler_4.6.0
## [59] withr_3.0.2
## [60] fontquiver_0.2.1
## [61] bit64_4.8.2
## [62] S7_0.2.2
## [63] BiocParallel_1.47.0
## [64] DBI_1.3.0
## [65] gplots_3.3.0
## [66] ggforce_0.5.0
## [67] MASS_7.3-65
## [68] ChIPseeker_1.49.0
## [69] rappdirs_0.3.4
## [70] DelayedArray_0.39.3
## [71] rjson_0.2.23
## [72] caTools_1.18.3
## [73] gtools_3.9.5
## [74] tools_4.6.0
## [75] otel_0.2.0
## [76] scatterpie_0.2.6
## [77] ape_5.8-1
## [78] glue_1.8.1
## [79] restfulr_0.0.16
## [80] nlme_3.1-169
## [81] GOSemSim_2.39.0
## [82] grid_4.6.0
## [83] gridBase_0.4-7
## [84] cluster_2.1.8.2
## [85] reshape2_1.4.5
## [86] generics_0.1.4
## [87] BSgenome_1.81.0
## [88] gtable_0.3.6
## [89] tzdb_0.5.0
## [90] seqPattern_1.45.0
## [91] tidyr_1.3.2
## [92] hms_1.1.4
## [93] data.table_1.18.4
## [94] XVector_0.53.0
## [95] BiocGenerics_0.59.6
## [96] ggrepel_0.9.8
## [97] BiocVersion_3.24.0
## [98] pillar_1.11.1
## [99] stringr_1.6.0
## [100] yulab.utils_0.2.4
## [101] tweenr_2.0.3
## [102] dplyr_1.2.1
## [103] treeio_1.37.0
## [104] BiocFileCache_3.3.0
## [105] lattice_0.22-9
## [106] rtracklayer_1.73.0
## [107] bit_4.6.0
## [108] tidyselect_1.2.1
## [109] fontLiberation_0.1.0
## [110] GO.db_3.23.1
## [111] maketools_1.3.2
## [112] Biostrings_2.81.2
## [113] knitr_1.51
## [114] fontBitstreamVera_0.1.1
## [115] IRanges_2.47.2
## [116] Seqinfo_1.3.0
## [117] SummarizedExperiment_1.43.0
## [118] stats4_4.6.0
## [119] xfun_0.57
## [120] Biobase_2.73.1
## [121] matrixStats_1.5.0
## [122] stringi_1.8.7
## [123] UCSC.utils_1.9.0
## [124] lazyeval_0.2.3
## [125] ggfun_0.2.0
## [126] yaml_2.3.12
## [127] boot_1.3-32
## [128] evaluate_1.0.5
## [129] codetools_0.2-20
## [130] cigarillo_1.3.0
## [131] gdtools_0.5.1
## [132] tibble_3.3.1
## [133] BiocManager_1.30.27
## [134] ggplotify_0.1.3
## [135] cli_3.6.6
## [136] systemfonts_1.3.2
## [137] jquerylib_0.1.4
## [138] Rcpp_1.1.1-1.1
## [139] GenomeInfoDb_1.49.1
## [140] dbplyr_2.5.2
## [141] png_0.1-9
## [142] XML_3.99-0.23
## [143] parallel_4.6.0
## [144] readr_2.2.0
## [145] ggplot2_4.0.3
## [146] blob_1.3.0
## [147] DOSE_4.7.0
## [148] bitops_1.0-9
## [149] viridisLite_0.4.3
## [150] tidytree_0.4.7
## [151] ggiraph_0.9.6
## [152] enrichit_0.1.4
## [153] scales_1.4.0
## [154] genomation_1.45.0
## [155] purrr_1.2.2
## [156] crayon_1.5.3
## [157] rlang_1.2.0
## [158] KEGGREST_1.53.0