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 4.4.0 RC (2024-04-16 r86441)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.4 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_1.7.5 BiocStyle_2.31.0
##
## loaded via a namespace (and not attached):
## [1] splines_4.4.0
## [2] BiocIO_1.13.0
## [3] bitops_1.0-7
## [4] ggplotify_0.1.2
## [5] filelock_1.0.3
## [6] tibble_3.2.1
## [7] polyclip_1.10-6
## [8] XML_3.99-0.16.1
## [9] lifecycle_1.0.4
## [10] lattice_0.22-6
## [11] MASS_7.3-60.2
## [12] magrittr_2.0.3
## [13] plotly_4.10.4
## [14] sass_0.4.9
## [15] rmarkdown_2.26
## [16] jquerylib_0.1.4
## [17] yaml_2.3.8
## [18] BRGenomics_1.15.0
## [19] plotrix_3.8-4
## [20] cowplot_1.1.3
## [21] DBI_1.2.2
## [22] RColorBrewer_1.1-3
## [23] abind_1.4-5
## [24] zlibbioc_1.49.3
## [25] GenomicRanges_1.55.4
## [26] purrr_1.0.2
## [27] ggraph_2.2.1
## [28] BiocGenerics_0.49.1
## [29] RCurl_1.98-1.14
## [30] yulab.utils_0.1.4
## [31] tweenr_2.0.3
## [32] rappdirs_0.3.3
## [33] GenomeInfoDbData_1.2.12
## [34] IRanges_2.37.1
## [35] S4Vectors_0.41.7
## [36] enrichplot_1.23.2
## [37] ggrepel_0.9.5
## [38] tidytree_0.4.6
## [39] pkgdown_2.0.9
## [40] ChIPseeker_1.39.0
## [41] codetools_0.2-20
## [42] DelayedArray_0.29.9
## [43] DOSE_3.29.2
## [44] ggforce_0.4.2
## [45] tidyselect_1.2.1
## [46] aplot_0.2.2
## [47] UCSC.utils_0.99.7
## [48] farver_2.1.1
## [49] viridis_0.6.5
## [50] matrixStats_1.3.0
## [51] stats4_4.4.0
## [52] BiocFileCache_2.11.2
## [53] GenomicAlignments_1.39.5
## [54] jsonlite_1.8.8
## [55] tidygraph_1.3.1
## [56] systemfonts_1.0.6
## [57] tools_4.4.0
## [58] treeio_1.27.1
## [59] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [60] ragg_1.3.0
## [61] Rcpp_1.0.12
## [62] glue_1.7.0
## [63] gridExtra_2.3
## [64] SparseArray_1.3.5
## [65] xfun_0.43
## [66] DESeq2_1.43.5
## [67] qvalue_2.35.0
## [68] MatrixGenerics_1.15.1
## [69] GenomeInfoDb_1.39.14
## [70] dplyr_1.1.4
## [71] withr_3.0.0
## [72] BiocManager_1.30.22
## [73] fastmap_1.1.1
## [74] boot_1.3-30
## [75] fansi_1.0.6
## [76] caTools_1.18.2
## [77] digest_0.6.35
## [78] R6_2.5.1
## [79] gridGraphics_0.5-1
## [80] seqPattern_1.35.0
## [81] textshaping_0.3.7
## [82] colorspace_2.1-0
## [83] GO.db_3.19.1
## [84] gtools_3.9.5
## [85] RSQLite_2.3.6
## [86] utf8_1.2.4
## [87] tidyr_1.3.1
## [88] generics_0.1.3
## [89] data.table_1.15.4
## [90] rtracklayer_1.63.2
## [91] graphlayouts_1.1.1
## [92] httr_1.4.7
## [93] htmlwidgets_1.6.4
## [94] S4Arrays_1.3.7
## [95] scatterpie_0.2.2
## [96] downloadthis_0.3.3
## [97] pkgconfig_2.0.3
## [98] gtable_0.3.5
## [99] blob_1.2.4
## [100] impute_1.77.0
## [101] XVector_0.43.1
## [102] shadowtext_0.1.3
## [103] htmltools_0.5.8.1
## [104] bookdown_0.39
## [105] fgsea_1.29.2
## [106] scales_1.3.0
## [107] Biobase_2.63.1
## [108] png_0.1-8
## [109] ggfun_0.1.4
## [110] knitr_1.46
## [111] tzdb_0.4.0
## [112] reshape2_1.4.4
## [113] rjson_0.2.21
## [114] nlme_3.1-164
## [115] curl_5.2.1
## [116] cachem_1.0.8
## [117] stringr_1.5.1
## [118] BiocVersion_3.19.1
## [119] KernSmooth_2.23-22
## [120] parallel_4.4.0
## [121] HDO.db_0.99.1
## [122] AnnotationDbi_1.65.2
## [123] restfulr_0.0.15
## [124] desc_1.4.3
## [125] pillar_1.9.0
## [126] grid_4.4.0
## [127] vctrs_0.6.5
## [128] gplots_3.1.3.1
## [129] dbplyr_2.5.0
## [130] evaluate_0.23
## [131] readr_2.1.5
## [132] GenomicFeatures_1.55.4
## [133] cli_3.6.2
## [134] locfit_1.5-9.9
## [135] compiler_4.4.0
## [136] Rsamtools_2.19.4
## [137] rlang_1.1.3
## [138] crayon_1.5.2
## [139] plyr_1.8.9
## [140] fs_1.6.4
## [141] stringi_1.8.3
## [142] genomation_1.35.0
## [143] viridisLite_0.4.2
## [144] gridBase_0.4-7
## [145] BiocParallel_1.37.1
## [146] munsell_0.5.1
## [147] Biostrings_2.71.6
## [148] lazyeval_0.2.2
## [149] GOSemSim_2.29.2
## [150] Matrix_1.7-0
## [151] BSgenome_1.71.4
## [152] hms_1.1.3
## [153] patchwork_1.2.0
## [154] bit64_4.0.5
## [155] ggplot2_3.5.1
## [156] KEGGREST_1.43.0
## [157] SummarizedExperiment_1.33.3
## [158] AnnotationHub_3.11.5
## [159] igraph_2.0.3
## [160] memoise_2.0.1
## [161] bslib_0.7.0
## [162] ggtree_3.11.2
## [163] fastmatch_1.1-4
## [164] bit_4.0.5
## [165] ape_5.8