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 4.2.1 (2022-06-23)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Ventura 13.0
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
##
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] EpiCompare_1.2.0 BiocStyle_2.26.0
##
## loaded via a namespace (and not attached):
## [1] utf8_1.2.2
## [2] tidyselect_1.1.2
## [3] htmlwidgets_1.5.4
## [4] RSQLite_2.2.14
## [5] AnnotationDbi_1.60.0
## [6] grid_4.2.1
## [7] BiocParallel_1.32.1
## [8] scatterpie_0.1.7
## [9] munsell_0.5.0
## [10] codetools_0.2-18
## [11] colorspace_2.0-3
## [12] GOSemSim_2.24.0
## [13] Biobase_2.58.0
## [14] filelock_1.0.2
## [15] highr_0.9
## [16] knitr_1.39
## [17] stats4_4.2.1
## [18] DOSE_3.24.1
## [19] labeling_0.4.2
## [20] MatrixGenerics_1.10.0
## [21] GenomeInfoDbData_1.2.8
## [22] polyclip_1.10-0
## [23] seqPattern_1.30.0
## [24] bit64_4.0.5
## [25] farver_2.1.1
## [26] vctrs_0.4.1
## [27] treeio_1.22.0
## [28] generics_0.1.3
## [29] xfun_0.31
## [30] BiocFileCache_2.6.0
## [31] R6_2.5.1
## [32] GenomeInfoDb_1.34.2
## [33] graphlayouts_0.8.0
## [34] locfit_1.5-9.6
## [35] bitops_1.0-7
## [36] BRGenomics_1.10.0
## [37] cachem_1.0.6
## [38] fgsea_1.24.0
## [39] gridGraphics_0.5-1
## [40] DelayedArray_0.24.0
## [41] assertthat_0.2.1
## [42] promises_1.2.0.1
## [43] BiocIO_1.8.0
## [44] scales_1.2.0
## [45] ggraph_2.0.5
## [46] enrichplot_1.18.0
## [47] gtable_0.3.0
## [48] tidygraph_1.2.1
## [49] rlang_1.0.4
## [50] genefilter_1.80.0
## [51] splines_4.2.1
## [52] rtracklayer_1.58.0
## [53] lazyeval_0.2.2
## [54] impute_1.72.0
## [55] BiocManager_1.30.18
## [56] yaml_2.3.5
## [57] reshape2_1.4.4
## [58] GenomicFeatures_1.50.2
## [59] httpuv_1.6.5
## [60] qvalue_2.30.0
## [61] tools_4.2.1
## [62] bookdown_0.27
## [63] ggplotify_0.1.0
## [64] gridBase_0.4-7
## [65] ggplot2_3.3.6
## [66] ellipsis_0.3.2
## [67] gplots_3.1.3
## [68] jquerylib_0.1.4
## [69] RColorBrewer_1.1-3
## [70] BiocGenerics_0.44.0
## [71] Rcpp_1.0.9
## [72] plyr_1.8.7
## [73] progress_1.2.2
## [74] zlibbioc_1.44.0
## [75] purrr_0.3.4
## [76] RCurl_1.98-1.7
## [77] prettyunits_1.1.1
## [78] viridis_0.6.2
## [79] cowplot_1.1.1
## [80] S4Vectors_0.36.0
## [81] SummarizedExperiment_1.28.0
## [82] ggrepel_0.9.1
## [83] magrittr_2.0.3
## [84] magick_2.7.3
## [85] data.table_1.14.2
## [86] matrixStats_0.62.0
## [87] hms_1.1.1
## [88] patchwork_1.1.1
## [89] mime_0.12
## [90] evaluate_0.15
## [91] xtable_1.8-4
## [92] HDO.db_0.99.1
## [93] XML_3.99-0.10
## [94] IRanges_2.32.0
## [95] gridExtra_2.3
## [96] compiler_4.2.1
## [97] biomaRt_2.54.0
## [98] tibble_3.1.7
## [99] KernSmooth_2.23-20
## [100] crayon_1.5.1
## [101] shadowtext_0.1.2
## [102] htmltools_0.5.2
## [103] ggfun_0.0.6
## [104] later_1.3.0
## [105] tzdb_0.3.0
## [106] tidyr_1.2.0
## [107] geneplotter_1.76.0
## [108] aplot_0.1.6
## [109] DBI_1.1.3
## [110] tweenr_1.0.2
## [111] ChIPseeker_1.34.0
## [112] genomation_1.30.0
## [113] dbplyr_2.2.1
## [114] MASS_7.3-58
## [115] rappdirs_0.3.3
## [116] boot_1.3-28
## [117] Matrix_1.4-1
## [118] readr_2.1.2
## [119] cli_3.3.0
## [120] parallel_4.2.1
## [121] igraph_1.3.5
## [122] GenomicRanges_1.50.1
## [123] pkgconfig_2.0.3
## [124] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [125] GenomicAlignments_1.34.0
## [126] plotly_4.10.0
## [127] xml2_1.3.3
## [128] ggtree_3.6.0
## [129] annotate_1.76.0
## [130] bslib_0.3.1
## [131] XVector_0.38.0
## [132] yulab.utils_0.0.5
## [133] stringr_1.4.0
## [134] digest_0.6.29
## [135] Biostrings_2.66.0
## [136] rmarkdown_2.14
## [137] fastmatch_1.1-3
## [138] tidytree_0.3.9
## [139] restfulr_0.0.15
## [140] curl_4.3.2
## [141] shiny_1.7.1
## [142] Rsamtools_2.14.0
## [143] gtools_3.9.3
## [144] rjson_0.2.21
## [145] lifecycle_1.0.1
## [146] nlme_3.1-158
## [147] jsonlite_1.8.0
## [148] viridisLite_0.4.0
## [149] BSgenome_1.66.1
## [150] fansi_1.0.3
## [151] pillar_1.7.0
## [152] lattice_0.20-45
## [153] KEGGREST_1.38.0
## [154] fastmap_1.1.0
## [155] httr_1.4.3
## [156] plotrix_3.8-2
## [157] survival_3.3-1
## [158] GO.db_3.15.0
## [159] interactiveDisplayBase_1.36.0
## [160] glue_1.6.2
## [161] png_0.1-7
## [162] BiocVersion_3.16.0
## [163] bit_4.0.4
## [164] ggforce_0.3.3
## [165] stringi_1.7.8
## [166] sass_0.4.1
## [167] blob_1.2.3
## [168] DESeq2_1.38.0
## [169] AnnotationHub_3.6.0
## [170] caTools_1.18.2
## [171] memoise_2.0.1
## [172] dplyr_1.0.9
## [173] ape_5.6-2