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 4.3.0 RC (2023-04-13 r84269)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.17-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_1.4.0 BiocStyle_2.28.0
##
## loaded via a namespace (and not attached):
## [1] splines_4.3.0
## [2] later_1.3.0
## [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_7.3-59
## [13] magrittr_2.0.3
## [14] plotly_4.10.1
## [15] sass_0.4.5
## [16] rmarkdown_2.21
## [17] jquerylib_0.1.4
## [18] yaml_2.3.7
## [19] BRGenomics_1.12.0
## [20] plotrix_3.8-2
## [21] httpuv_1.6.9
## [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_0.38.0
## [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_0.26.0
## [44] DOSE_3.26.0
## [45] xml2_1.3.3
## [46] ggforce_0.4.1
## [47] tidyselect_1.2.0
## [48] aplot_0.1.10
## [49] farver_2.1.1
## [50] viridis_0.6.2
## [51] base64enc_0.1-3
## [52] matrixStats_0.63.0
## [53] stats4_4.3.0
## [54] BiocFileCache_2.8.0
## [55] GenomicAlignments_1.36.0
## [56] jsonlite_1.8.4
## [57] ellipsis_0.3.2
## [58] tidygraph_1.2.3
## [59] tools_4.3.0
## [60] progress_1.2.2
## [61] treeio_1.24.0
## [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_1.40.0
## [68] qvalue_2.32.0
## [69] MatrixGenerics_1.12.0
## [70] GenomeInfoDb_1.36.0
## [71] dplyr_1.1.2
## [72] withr_2.5.0
## [73] BiocManager_1.30.20
## [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_2.56.0
## [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_0.8.4
## [98] httr_1.4.5
## [99] scatterpie_0.1.9
## [100] downloadthis_0.3.2
## [101] pkgconfig_2.0.3
## [102] gtable_0.3.3
## [103] blob_1.2.4
## [104] impute_1.74.0
## [105] XVector_0.40.0
## [106] shadowtext_0.1.2
## [107] htmltools_0.5.5
## [108] bookdown_0.33
## [109] fgsea_1.26.0
## [110] scales_1.2.1
## [111] Biobase_2.60.0
## [112] png_0.1-8
## [113] ggfun_0.0.9
## [114] knitr_1.42
## [115] tzdb_0.3.0
## [116] reshape2_1.4.4
## [117] rjson_0.2.21
## [118] nlme_3.1-162
## [119] curl_5.0.0
## [120] cachem_1.0.7
## [121] stringr_1.5.0
## [122] BiocVersion_3.17.1
## [123] KernSmooth_2.23-20
## [124] parallel_4.3.0
## [125] HDO.db_0.99.1
## [126] AnnotationDbi_1.62.0
## [127] restfulr_0.0.15
## [128] pillar_1.9.0
## [129] grid_4.3.0
## [130] vctrs_0.6.2
## [131] gplots_3.1.3
## [132] promises_1.2.0.1
## [133] dbplyr_2.3.2
## [134] xtable_1.8-4
## [135] evaluate_0.20
## [136] magick_2.7.4
## [137] readr_2.1.4
## [138] GenomicFeatures_1.52.0
## [139] cli_3.6.1
## [140] locfit_1.5-9.7
## [141] compiler_4.3.0
## [142] Rsamtools_2.16.0
## [143] rlang_1.1.0
## [144] crayon_1.5.2
## [145] labeling_0.4.2
## [146] fs_1.6.2
## [147] plyr_1.8.8
## [148] stringi_1.7.12
## [149] gridBase_0.4-7
## [150] genomation_1.32.0
## [151] viridisLite_0.4.1
## [152] BiocParallel_1.34.0
## [153] munsell_0.5.0
## [154] Biostrings_2.68.0
## [155] lazyeval_0.2.2
## [156] GOSemSim_2.26.0
## [157] Matrix_1.5-4
## [158] BSgenome_1.68.0
## [159] hms_1.1.3
## [160] patchwork_1.1.2
## [161] bit64_4.0.5
## [162] ggplot2_3.4.2
## [163] KEGGREST_1.40.0
## [164] shiny_1.7.4
## [165] highr_0.10
## [166] SummarizedExperiment_1.30.0
## [167] interactiveDisplayBase_1.38.0
## [168] AnnotationHub_3.8.0
## [169] igraph_1.4.2
## [170] memoise_2.0.1
## [171] bslib_0.4.2
## [172] ggtree_3.8.0
## [173] fastmatch_1.1-3
## [174] bit_4.0.5
## [175] ape_5.7-1