vignettes/docker.Rmd
docker.Rmdepicompare 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 4.4.1 (2024-06-14)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.5 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [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: UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] EpiCompare_1.9.10 BiocStyle_2.33.1
##
## loaded via a namespace (and not attached):
## [1] splines_4.4.1
## [2] BiocIO_1.15.2
## [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] polyclip_1.10-7
## [9] XML_3.99-0.17
## [10] lifecycle_1.0.4
## [11] lattice_0.22-6
## [12] MASS_7.3-61
## [13] magrittr_2.0.3
## [14] plotly_4.10.4
## [15] sass_0.4.9
## [16] rmarkdown_2.28
## [17] jquerylib_0.1.4
## [18] yaml_2.3.10
## [19] plotrix_3.8-4
## [20] cowplot_1.1.3
## [21] DBI_1.2.3
## [22] RColorBrewer_1.1-3
## [23] abind_1.4-8
## [24] zlibbioc_1.51.1
## [25] GenomicRanges_1.57.2
## [26] purrr_1.0.2
## [27] R.utils_2.12.3
## [28] ggraph_2.2.1
## [29] BiocGenerics_0.51.3
## [30] RCurl_1.98-1.16
## [31] yulab.utils_0.1.7
## [32] tweenr_2.0.3
## [33] rappdirs_0.3.3
## [34] GenomeInfoDbData_1.2.13
## [35] IRanges_2.39.2
## [36] S4Vectors_0.43.2
## [37] enrichplot_1.25.3
## [38] ggrepel_0.9.6
## [39] tidytree_0.4.6
## [40] pkgdown_2.1.1
## [41] ChIPseeker_1.41.3
## [42] codetools_0.2-20
## [43] DelayedArray_0.31.14
## [44] DOSE_3.99.1
## [45] ggforce_0.4.2
## [46] tidyselect_1.2.1
## [47] aplot_0.2.3
## [48] UCSC.utils_1.1.0
## [49] farver_2.1.2
## [50] viridis_0.6.5
## [51] matrixStats_1.4.1
## [52] stats4_4.4.1
## [53] BiocFileCache_2.13.2
## [54] GenomicAlignments_1.41.0
## [55] jsonlite_1.8.9
## [56] tidygraph_1.3.1
## [57] systemfonts_1.1.0
## [58] tools_4.4.1
## [59] treeio_1.29.1
## [60] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [61] ragg_1.3.3
## [62] Rcpp_1.0.13
## [63] glue_1.8.0
## [64] gridExtra_2.3
## [65] SparseArray_1.5.44
## [66] xfun_0.48
## [67] qvalue_2.37.0
## [68] MatrixGenerics_1.17.0
## [69] GenomeInfoDb_1.41.2
## [70] dplyr_1.1.4
## [71] withr_3.0.1
## [72] BiocManager_1.30.25
## [73] fastmap_1.2.0
## [74] boot_1.3-31
## [75] fansi_1.0.6
## [76] caTools_1.18.3
## [77] digest_0.6.37
## [78] R6_2.5.1
## [79] gridGraphics_0.5-1
## [80] seqPattern_1.37.0
## [81] textshaping_0.4.0
## [82] colorspace_2.1-1
## [83] GO.db_3.20.0
## [84] gtools_3.9.5
## [85] RSQLite_2.3.7
## [86] R.methodsS3_1.8.2
## [87] utf8_1.2.4
## [88] tidyr_1.3.1
## [89] generics_0.1.3
## [90] data.table_1.16.2
## [91] rtracklayer_1.65.0
## [92] graphlayouts_1.2.0
## [93] httr_1.4.7
## [94] htmlwidgets_1.6.4
## [95] S4Arrays_1.5.11
## [96] scatterpie_0.2.4
## [97] downloadthis_0.4.1
## [98] pkgconfig_2.0.3
## [99] gtable_0.3.5
## [100] blob_1.2.4
## [101] impute_1.79.0
## [102] XVector_0.45.0
## [103] shadowtext_0.1.4
## [104] htmltools_0.5.8.1
## [105] bookdown_0.41
## [106] fgsea_1.31.6
## [107] scales_1.3.0
## [108] Biobase_2.65.1
## [109] png_0.1-8
## [110] ggfun_0.1.6
## [111] knitr_1.48
## [112] tzdb_0.4.0
## [113] reshape2_1.4.4
## [114] rjson_0.2.23
## [115] nlme_3.1-166
## [116] curl_5.2.3
## [117] cachem_1.1.0
## [118] stringr_1.5.1
## [119] BiocVersion_3.20.0
## [120] KernSmooth_2.23-24
## [121] parallel_4.4.1
## [122] AnnotationDbi_1.67.0
## [123] restfulr_0.0.15
## [124] desc_1.4.3
## [125] pillar_1.9.0
## [126] grid_4.4.1
## [127] vctrs_0.6.5
## [128] gplots_3.2.0
## [129] dbplyr_2.5.0
## [130] evaluate_1.0.1
## [131] readr_2.1.5
## [132] GenomicFeatures_1.57.1
## [133] cli_3.6.3
## [134] compiler_4.4.1
## [135] Rsamtools_2.21.2
## [136] rlang_1.1.4
## [137] crayon_1.5.3
## [138] plyr_1.8.9
## [139] fs_1.6.4
## [140] stringi_1.8.4
## [141] genomation_1.37.0
## [142] viridisLite_0.4.2
## [143] gridBase_0.4-7
## [144] BiocParallel_1.39.0
## [145] munsell_0.5.1
## [146] Biostrings_2.73.2
## [147] lazyeval_0.2.2
## [148] GOSemSim_2.31.2
## [149] Matrix_1.7-0
## [150] BSgenome_1.73.1
## [151] hms_1.1.3
## [152] patchwork_1.3.0
## [153] bit64_4.5.2
## [154] ggplot2_3.5.1
## [155] KEGGREST_1.45.1
## [156] SummarizedExperiment_1.35.4
## [157] AnnotationHub_3.13.3
## [158] igraph_2.0.3
## [159] memoise_2.0.1
## [160] bslib_0.8.0
## [161] ggtree_3.13.1
## [162] fastmatch_1.1-4
## [163] bit_4.5.0
## [164] ape_5.8