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 version 4.3.3 (2024-02-29)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.18-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
##
## 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_1.6.7 BiocStyle_2.30.0
##
## loaded via a namespace (and not attached):
## [1] splines_4.3.3
## [2] later_1.3.2
## [3] BiocIO_1.12.0
## [4] bitops_1.0-7
## [5] ggplotify_0.1.2
## [6] filelock_1.0.3
## [7] tibble_3.2.1
## [8] polyclip_1.10-6
## [9] XML_3.99-0.16.1
## [10] lifecycle_1.0.4
## [11] lattice_0.22-6
## [12] MASS_7.3-60.0.1
## [13] magrittr_2.0.3
## [14] plotly_4.10.4
## [15] sass_0.4.9
## [16] rmarkdown_2.26
## [17] plotrix_3.8-4
## [18] jquerylib_0.1.4
## [19] yaml_2.3.8
## [20] BRGenomics_1.14.1
## [21] httpuv_1.6.14
## [22] cowplot_1.1.3
## [23] DBI_1.2.2
## [24] RColorBrewer_1.1-3
## [25] lubridate_1.9.3
## [26] abind_1.4-5
## [27] zlibbioc_1.48.2
## [28] GenomicRanges_1.54.1
## [29] purrr_1.0.2
## [30] ggraph_2.2.1
## [31] BiocGenerics_0.48.1
## [32] RCurl_1.98-1.14
## [33] yulab.utils_0.1.4
## [34] tweenr_2.0.3
## [35] rappdirs_0.3.3
## [36] GenomeInfoDbData_1.2.11
## [37] IRanges_2.36.0
## [38] S4Vectors_0.40.2
## [39] enrichplot_1.22.0
## [40] ggrepel_0.9.5
## [41] tidytree_0.4.6
## [42] ChIPseeker_1.38.0
## [43] codetools_0.2-19
## [44] DelayedArray_0.28.0
## [45] DOSE_3.28.2
## [46] xml2_1.3.6
## [47] ggforce_0.4.2
## [48] tidyselect_1.2.1
## [49] aplot_0.2.2
## [50] farver_2.1.1
## [51] viridis_0.6.5
## [52] base64enc_0.1-3
## [53] matrixStats_1.2.0
## [54] stats4_4.3.3
## [55] BiocFileCache_2.10.1
## [56] GenomicAlignments_1.38.2
## [57] jsonlite_1.8.8
## [58] ellipsis_0.3.2
## [59] tidygraph_1.3.1
## [60] tools_4.3.3
## [61] progress_1.2.3
## [62] treeio_1.26.0
## [63] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [64] Rcpp_1.0.12
## [65] glue_1.7.0
## [66] gridExtra_2.3
## [67] SparseArray_1.2.4
## [68] xfun_0.42
## [69] DESeq2_1.42.1
## [70] qvalue_2.34.0
## [71] MatrixGenerics_1.14.0
## [72] GenomeInfoDb_1.38.8
## [73] dplyr_1.1.4
## [74] withr_3.0.0
## [75] BiocManager_1.30.22
## [76] fastmap_1.1.1
## [77] boot_1.3-30
## [78] fansi_1.0.6
## [79] caTools_1.18.2
## [80] digest_0.6.35
## [81] timechange_0.3.0
## [82] R6_2.5.1
## [83] mime_0.12
## [84] gridGraphics_0.5-1
## [85] seqPattern_1.34.0
## [86] colorspace_2.1-0
## [87] GO.db_3.18.0
## [88] gtools_3.9.5
## [89] biomaRt_2.58.2
## [90] RSQLite_2.3.5
## [91] utf8_1.2.4
## [92] tidyr_1.3.1
## [93] generics_0.1.3
## [94] data.table_1.15.2
## [95] bsplus_0.1.4
## [96] rtracklayer_1.62.0
## [97] htmlwidgets_1.6.4
## [98] prettyunits_1.2.0
## [99] graphlayouts_1.1.1
## [100] httr_1.4.7
## [101] S4Arrays_1.2.1
## [102] downloadthis_0.3.3
## [103] scatterpie_0.2.1
## [104] pkgconfig_2.0.3
## [105] gtable_0.3.4
## [106] blob_1.2.4
## [107] impute_1.76.0
## [108] XVector_0.42.0
## [109] shadowtext_0.1.3
## [110] htmltools_0.5.7
## [111] bookdown_0.38
## [112] fgsea_1.28.0
## [113] scales_1.3.0
## [114] Biobase_2.62.0
## [115] png_0.1-8
## [116] ggfun_0.1.4
## [117] knitr_1.45
## [118] tzdb_0.4.0
## [119] reshape2_1.4.4
## [120] rjson_0.2.21
## [121] nlme_3.1-164
## [122] curl_5.2.1
## [123] cachem_1.0.8
## [124] stringr_1.5.1
## [125] KernSmooth_2.23-22
## [126] BiocVersion_3.18.1
## [127] parallel_4.3.3
## [128] HDO.db_0.99.1
## [129] AnnotationDbi_1.64.1
## [130] restfulr_0.0.15
## [131] pillar_1.9.0
## [132] grid_4.3.3
## [133] vctrs_0.6.5
## [134] gplots_3.1.3.1
## [135] promises_1.2.1
## [136] dbplyr_2.5.0
## [137] xtable_1.8-4
## [138] evaluate_0.23
## [139] magick_2.8.3
## [140] readr_2.1.5
## [141] GenomicFeatures_1.54.4
## [142] cli_3.6.2
## [143] locfit_1.5-9.9
## [144] compiler_4.3.3
## [145] Rsamtools_2.18.0
## [146] rlang_1.1.3
## [147] crayon_1.5.2
## [148] labeling_0.4.3
## [149] plyr_1.8.9
## [150] fs_1.6.3
## [151] stringi_1.8.3
## [152] gridBase_0.4-7
## [153] genomation_1.34.0
## [154] viridisLite_0.4.2
## [155] BiocParallel_1.36.0
## [156] munsell_0.5.0
## [157] Biostrings_2.70.3
## [158] lazyeval_0.2.2
## [159] GOSemSim_2.28.1
## [160] Matrix_1.6-5
## [161] BSgenome_1.70.2
## [162] hms_1.1.3
## [163] patchwork_1.2.0
## [164] bit64_4.0.5
## [165] ggplot2_3.5.0
## [166] KEGGREST_1.42.0
## [167] shiny_1.8.0
## [168] highr_0.10
## [169] SummarizedExperiment_1.32.0
## [170] interactiveDisplayBase_1.40.0
## [171] AnnotationHub_3.10.0
## [172] igraph_2.0.3
## [173] memoise_2.0.1
## [174] bslib_0.6.1
## [175] ggtree_3.10.1
## [176] fastmatch_1.1-4
## [177] bit_4.0.5
## [178] ape_5.7-1