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/epicompare
Once 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/epicompare
Finally, 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 version 4.3.0 RC (2023-04-13 r84257)
## Platform: x86_64-apple-darwin20 (64-bit)
## Running under: macOS Monterey 12.6.4
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
##
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## time zone: America/New_York
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] EpiCompare_1.4.0 BiocStyle_2.28.0
##
## loaded via a namespace (and not attached):
## [1] splines_4.3.0
## [2] later_1.3.1
## [3] BiocIO_1.10.0
## [4] bitops_1.0-7
## [5] ggplotify_0.1.0
## [6] filelock_1.0.2
## [7] tibble_3.2.1
## [8] polyclip_1.10-4
## [9] XML_3.99-0.14
## [10] lifecycle_1.0.3
## [11] lattice_0.21-8
## [12] MASS_7.3-60
## [13] magrittr_2.0.3
## [14] plotly_4.10.2
## [15] sass_0.4.6
## [16] rmarkdown_2.22
## [17] jquerylib_0.1.4
## [18] yaml_2.3.7
## [19] BRGenomics_1.12.0
## [20] plotrix_3.8-2
## [21] httpuv_1.6.11
## [22] cowplot_1.1.1
## [23] DBI_1.1.3
## [24] RColorBrewer_1.1-3
## [25] lubridate_1.9.2
## [26] zlibbioc_1.46.0
## [27] GenomicRanges_1.52.0
## [28] purrr_1.0.1
## [29] ggraph_2.1.0
## [30] BiocGenerics_0.46.0
## [31] RCurl_1.98-1.12
## [32] yulab.utils_0.0.6
## [33] tweenr_2.0.2
## [34] rappdirs_0.3.3
## [35] GenomeInfoDbData_1.2.10
## [36] IRanges_2.34.0
## [37] S4Vectors_0.38.1
## [38] enrichplot_1.20.0
## [39] ggrepel_0.9.3
## [40] tidytree_0.4.2
## [41] ChIPseeker_1.36.0
## [42] codetools_0.2-19
## [43] DelayedArray_0.26.3
## [44] DOSE_3.26.1
## [45] xml2_1.3.4
## [46] ggforce_0.4.1
## [47] tidyselect_1.2.0
## [48] aplot_0.1.10
## [49] farver_2.1.1
## [50] viridis_0.6.3
## [51] base64enc_0.1-3
## [52] matrixStats_1.0.0
## [53] stats4_4.3.0
## [54] BiocFileCache_2.8.0
## [55] GenomicAlignments_1.36.0
## [56] jsonlite_1.8.5
## [57] ellipsis_0.3.2
## [58] tidygraph_1.2.3
## [59] tools_4.3.0
## [60] progress_1.2.2
## [61] treeio_1.24.1
## [62] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [63] Rcpp_1.0.10
## [64] glue_1.6.2
## [65] gridExtra_2.3
## [66] xfun_0.39
## [67] DESeq2_1.40.1
## [68] qvalue_2.32.0
## [69] MatrixGenerics_1.12.2
## [70] GenomeInfoDb_1.36.0
## [71] dplyr_1.1.2
## [72] withr_2.5.0
## [73] BiocManager_1.30.21
## [74] fastmap_1.1.1
## [75] boot_1.3-28.1
## [76] fansi_1.0.4
## [77] caTools_1.18.2
## [78] digest_0.6.31
## [79] timechange_0.2.0
## [80] R6_2.5.1
## [81] mime_0.12
## [82] gridGraphics_0.5-1
## [83] seqPattern_1.32.0
## [84] colorspace_2.1-0
## [85] GO.db_3.17.0
## [86] gtools_3.9.4
## [87] biomaRt_2.56.1
## [88] RSQLite_2.3.1
## [89] utf8_1.2.3
## [90] tidyr_1.3.0
## [91] generics_0.1.3
## [92] data.table_1.14.8
## [93] bsplus_0.1.4
## [94] rtracklayer_1.60.0
## [95] htmlwidgets_1.6.2
## [96] prettyunits_1.1.1
## [97] graphlayouts_1.0.0
## [98] httr_1.4.6
## [99] S4Arrays_1.0.4
## [100] downloadthis_0.3.2
## [101] scatterpie_0.2.1
## [102] pkgconfig_2.0.3
## [103] gtable_0.3.3
## [104] blob_1.2.4
## [105] impute_1.74.1
## [106] XVector_0.40.0
## [107] shadowtext_0.1.2
## [108] htmltools_0.5.5
## [109] bookdown_0.34
## [110] fgsea_1.26.0
## [111] scales_1.2.1
## [112] Biobase_2.60.0
## [113] png_0.1-8
## [114] ggfun_0.0.9
## [115] knitr_1.43
## [116] tzdb_0.4.0
## [117] reshape2_1.4.4
## [118] rjson_0.2.21
## [119] nlme_3.1-162
## [120] curl_5.0.1
## [121] cachem_1.0.8
## [122] stringr_1.5.0
## [123] BiocVersion_3.17.1
## [124] KernSmooth_2.23-21
## [125] parallel_4.3.0
## [126] HDO.db_0.99.1
## [127] AnnotationDbi_1.62.1
## [128] restfulr_0.0.15
## [129] pillar_1.9.0
## [130] grid_4.3.0
## [131] vctrs_0.6.2
## [132] gplots_3.1.3
## [133] promises_1.2.0.1
## [134] dbplyr_2.3.2
## [135] xtable_1.8-4
## [136] evaluate_0.21
## [137] magick_2.7.4
## [138] readr_2.1.4
## [139] GenomicFeatures_1.52.0
## [140] cli_3.6.1
## [141] locfit_1.5-9.8
## [142] compiler_4.3.0
## [143] Rsamtools_2.16.0
## [144] rlang_1.1.1
## [145] crayon_1.5.2
## [146] labeling_0.4.2
## [147] fs_1.6.2
## [148] plyr_1.8.8
## [149] stringi_1.7.12
## [150] gridBase_0.4-7
## [151] genomation_1.32.0
## [152] viridisLite_0.4.2
## [153] BiocParallel_1.34.2
## [154] munsell_0.5.0
## [155] Biostrings_2.68.1
## [156] lazyeval_0.2.2
## [157] GOSemSim_2.26.0
## [158] Matrix_1.5-4.1
## [159] BSgenome_1.68.0
## [160] hms_1.1.3
## [161] patchwork_1.1.2
## [162] bit64_4.0.5
## [163] ggplot2_3.4.2
## [164] KEGGREST_1.40.0
## [165] shiny_1.7.4
## [166] highr_0.10
## [167] SummarizedExperiment_1.30.2
## [168] interactiveDisplayBase_1.38.0
## [169] AnnotationHub_3.8.0
## [170] igraph_1.4.3
## [171] memoise_2.0.1
## [172] bslib_0.5.0
## [173] ggtree_3.8.0
## [174] fastmatch_1.1-3
## [175] bit_4.0.5
## [176] ape_5.7-1