vignettes/docker.Rmd
docker.RmdMultiEWCE is now available via ghcr.io 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 ghcr.io/neurogenomics/MultiEWCEOnce 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 8900:8787 \
ghcr.io/neurogenomics/MultiEWCE<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://ghcr.io/neurogenomics/MultiEWCEFor troubleshooting, see the Singularity documentation.
Finally, launch the containerised Rstudio by entering the following URL in any web browser: http://localhost:8900/
Login using the credentials set during the Installation steps.
utils::sessionInfo()## R Under development (unstable) (2023-11-08 r85496)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.3 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] MultiEWCE_0.1.9 BiocStyle_2.31.0
##
## loaded via a namespace (and not attached):
## [1] later_1.3.1 bitops_1.0-7
## [3] ggplotify_0.1.2 GeneOverlap_1.39.0
## [5] filelock_1.0.2 tibble_3.2.1
## [7] ontologyPlot_1.6 ggnetwork_0.5.12
## [9] graph_1.81.0 lifecycle_1.0.4
## [11] rstatix_0.7.2 HPOExplorer_0.99.12
## [13] rprojroot_2.0.4 lattice_0.22-5
## [15] backports_1.4.1 magrittr_2.0.3
## [17] limma_3.59.1 plotly_4.10.3
## [19] sass_0.4.7 rmarkdown_2.25
## [21] jquerylib_0.1.4 yaml_2.3.7
## [23] httpuv_1.6.12 HGNChelper_0.8.1
## [25] DBI_1.1.3 RColorBrewer_1.1-3
## [27] abind_1.4-5 zlibbioc_1.49.0
## [29] GenomicRanges_1.55.1 purrr_1.0.2
## [31] BiocGenerics_0.49.1 RCurl_1.98-1.13
## [33] yulab.utils_0.1.0 rappdirs_0.3.3
## [35] GenomeInfoDbData_1.2.11 IRanges_2.37.0
## [37] S4Vectors_0.41.1 tidytree_0.4.5
## [39] piggyback_0.1.5 pkgdown_2.0.7
## [41] DelayedArray_0.29.0 tidyselect_1.2.0
## [43] aplot_0.2.2 matrixStats_1.1.0
## [45] stats4_4.4.0 BiocFileCache_2.11.1
## [47] jsonlite_1.8.7 ellipsis_0.3.2
## [49] systemfonts_1.0.5 paintmap_1.0
## [51] tools_4.4.0 treeio_1.27.0
## [53] ragg_1.2.6 Rcpp_1.0.11
## [55] glue_1.6.2 SparseArray_1.3.1
## [57] xfun_0.41 MatrixGenerics_1.15.0
## [59] GenomeInfoDb_1.39.1 RNOmni_1.0.1.2
## [61] dplyr_1.1.3 BiocManager_1.30.22
## [63] fastmap_1.1.1 fansi_1.0.5
## [65] caTools_1.18.2 digest_0.6.33
## [67] R6_2.5.1 mime_0.12
## [69] gridGraphics_0.5-1 textshaping_0.3.7
## [71] colorspace_2.1-0 gtools_3.9.4
## [73] RSQLite_2.3.3 utf8_1.2.4
## [75] tidyr_1.3.0 generics_0.1.3
## [77] data.table_1.14.8 httr_1.4.7
## [79] htmlwidgets_1.6.2 S4Arrays_1.3.0
## [81] ontologyIndex_2.11 pkgconfig_2.0.3
## [83] gtable_0.3.4 blob_1.2.4
## [85] SingleCellExperiment_1.25.0 XVector_0.43.0
## [87] htmltools_0.5.7 carData_3.0-5
## [89] bookdown_0.36 scales_1.2.1
## [91] Biobase_2.63.0 png_0.1-8
## [93] ggfun_0.1.3 knitr_1.45
## [95] reshape2_1.4.4 coda_0.19-4
## [97] statnet.common_4.9.0 nlme_3.1-163
## [99] curl_5.1.0 cachem_1.0.8
## [101] stringr_1.5.0 BiocVersion_3.19.1
## [103] KernSmooth_2.23-22 parallel_4.4.0
## [105] AnnotationDbi_1.65.2 desc_1.4.2
## [107] pillar_1.9.0 grid_4.4.0
## [109] vctrs_0.6.4 gplots_3.1.3
## [111] promises_1.2.1 ggpubr_0.6.0
## [113] car_3.1-2 dbplyr_2.4.0
## [115] xtable_1.8-4 Rgraphviz_2.47.0
## [117] evaluate_0.23 orthogene_1.9.0
## [119] cli_3.6.1 compiler_4.4.0
## [121] rlang_1.1.2 crayon_1.5.2
## [123] grr_0.9.5 ggsignif_0.6.4
## [125] gprofiler2_0.2.2 EWCE_1.11.2
## [127] plyr_1.8.9 fs_1.6.3
## [129] stringi_1.8.1 viridisLite_0.4.2
## [131] ewceData_1.11.0 network_1.18.1
## [133] babelgene_22.9 munsell_0.5.0
## [135] Biostrings_2.71.1 lazyeval_0.2.2
## [137] homologene_1.4.68.19.3.27 Matrix_1.6-2
## [139] ExperimentHub_2.11.0 patchwork_1.1.3
## [141] bit64_4.0.5 ggplot2_3.4.4
## [143] KEGGREST_1.43.0 statmod_1.5.0
## [145] shiny_1.7.5.1 SummarizedExperiment_1.33.0
## [147] interactiveDisplayBase_1.41.0 AnnotationHub_3.11.0
## [149] broom_1.0.5 memoise_2.0.1
## [151] bslib_0.5.1 ggtree_3.11.0
## [153] bit_4.0.5 ape_5.7-1