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.
utils::sessionInfo()## R Under development (unstable) (2024-10-21 r87258)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.1 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.21-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [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: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] EpiCompare_1.11.0 BiocStyle_2.35.0
##
## loaded via a namespace (and not attached):
## [1] splines_4.5.0
## [2] BiocIO_1.17.0
## [3] bitops_1.0-9
## [4] ggplotify_0.1.2
## [5] filelock_1.0.3
## [6] tibble_3.2.1
## [7] R.oo_1.26.0
## [8] XML_3.99-0.17
## [9] lifecycle_1.0.4
## [10] lattice_0.22-6
## [11] magrittr_2.0.3
## [12] plotly_4.10.4
## [13] sass_0.4.9
## [14] rmarkdown_2.28
## [15] jquerylib_0.1.4
## [16] yaml_2.3.10
## [17] plotrix_3.8-4
## [18] ggtangle_0.0.3
## [19] cowplot_1.1.3
## [20] DBI_1.2.3
## [21] RColorBrewer_1.1-3
## [22] lubridate_1.9.3
## [23] abind_1.4-8
## [24] zlibbioc_1.53.0
## [25] GenomicRanges_1.59.0
## [26] purrr_1.0.2
## [27] R.utils_2.12.3
## [28] BiocGenerics_0.53.0
## [29] RCurl_1.98-1.16
## [30] yulab.utils_0.1.7
## [31] rappdirs_0.3.3
## [32] GenomeInfoDbData_1.2.13
## [33] IRanges_2.41.0
## [34] S4Vectors_0.45.0
## [35] enrichplot_1.27.0
## [36] ggrepel_0.9.6
## [37] tidytree_0.4.6
## [38] ChIPseeker_1.43.0
## [39] codetools_0.2-20
## [40] DelayedArray_0.33.0
## [41] DOSE_4.1.0
## [42] tidyselect_1.2.1
## [43] aplot_0.2.3
## [44] UCSC.utils_1.3.0
## [45] farver_2.1.2
## [46] matrixStats_1.4.1
## [47] stats4_4.5.0
## [48] BiocFileCache_2.15.0
## [49] GenomicAlignments_1.43.0
## [50] jsonlite_1.8.9
## [51] tools_4.5.0
## [52] treeio_1.31.0
## [53] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [54] Rcpp_1.0.13
## [55] glue_1.8.0
## [56] SparseArray_1.7.0
## [57] xfun_0.48
## [58] qvalue_2.39.0
## [59] MatrixGenerics_1.19.0
## [60] GenomeInfoDb_1.43.0
## [61] dplyr_1.1.4
## [62] withr_3.0.2
## [63] BiocManager_1.30.25
## [64] fastmap_1.2.0
## [65] boot_1.3-31
## [66] fansi_1.0.6
## [67] caTools_1.18.3
## [68] digest_0.6.37
## [69] timechange_0.3.0
## [70] R6_2.5.1
## [71] mime_0.12
## [72] gridGraphics_0.5-1
## [73] seqPattern_1.39.0
## [74] colorspace_2.1-1
## [75] GO.db_3.20.0
## [76] gtools_3.9.5
## [77] RSQLite_2.3.7
## [78] R.methodsS3_1.8.2
## [79] b64_0.1.3
## [80] utf8_1.2.4
## [81] tidyr_1.3.1
## [82] generics_0.1.3
## [83] data.table_1.16.2
## [84] rtracklayer_1.67.0
## [85] bsplus_0.1.4
## [86] httr_1.4.7
## [87] htmlwidgets_1.6.4
## [88] S4Arrays_1.7.0
## [89] downloadthis_0.4.1
## [90] pkgconfig_2.0.3
## [91] gtable_0.3.6
## [92] blob_1.2.4
## [93] impute_1.81.0
## [94] XVector_0.47.0
## [95] htmltools_0.5.8.1
## [96] bookdown_0.41
## [97] fgsea_1.33.0
## [98] scales_1.3.0
## [99] Biobase_2.67.0
## [100] png_0.1-8
## [101] ggfun_0.1.7
## [102] knitr_1.48
## [103] tzdb_0.4.0
## [104] reshape2_1.4.4
## [105] rjson_0.2.23
## [106] nlme_3.1-166
## [107] curl_5.2.3
## [108] cachem_1.1.0
## [109] stringr_1.5.1
## [110] BiocVersion_3.21.1
## [111] KernSmooth_2.23-24
## [112] parallel_4.5.0
## [113] AnnotationDbi_1.69.0
## [114] restfulr_0.0.15
## [115] pillar_1.9.0
## [116] grid_4.5.0
## [117] vctrs_0.6.5
## [118] gplots_3.2.0
## [119] dbplyr_2.5.0
## [120] evaluate_1.0.1
## [121] magick_2.8.5
## [122] tinytex_0.53
## [123] readr_2.1.5
## [124] GenomicFeatures_1.59.0
## [125] cli_3.6.3
## [126] compiler_4.5.0
## [127] Rsamtools_2.23.0
## [128] rlang_1.1.4
## [129] crayon_1.5.3
## [130] labeling_0.4.3
## [131] plyr_1.8.9
## [132] fs_1.6.4
## [133] stringi_1.8.4
## [134] genomation_1.39.0
## [135] viridisLite_0.4.2
## [136] gridBase_0.4-7
## [137] BiocParallel_1.41.0
## [138] munsell_0.5.1
## [139] Biostrings_2.75.0
## [140] lazyeval_0.2.2
## [141] GOSemSim_2.33.0
## [142] Matrix_1.7-1
## [143] BSgenome_1.75.0
## [144] hms_1.1.3
## [145] patchwork_1.3.0
## [146] bit64_4.5.2
## [147] ggplot2_3.5.1
## [148] KEGGREST_1.47.0
## [149] SummarizedExperiment_1.37.0
## [150] highr_0.11
## [151] AnnotationHub_3.15.0
## [152] igraph_2.1.1
## [153] memoise_2.0.1
## [154] bslib_0.8.0
## [155] ggtree_3.15.0
## [156] fastmatch_1.1-4
## [157] bit_4.5.0
## [158] ape_5.8