orthogene 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/orthogene
Once 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/orthogene
<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/orthogene
For 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 version 4.5.1 Patched (2025-08-23 r88802)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.3 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.22-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0 LAPACK version 3.12.0
##
## 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] orthogene_1.15.02 BiocStyle_2.37.1
##
## loaded via a namespace (and not attached):
## [1] gtable_0.3.6 babelgene_22.9
## [3] xfun_0.53 bslib_0.9.0
## [5] ggplot2_4.0.0 htmlwidgets_1.6.4
## [7] rstatix_0.7.2 lattice_0.22-7
## [9] vctrs_0.6.5 tools_4.5.1
## [11] generics_0.1.4 yulab.utils_0.2.1
## [13] parallel_4.5.1 tibble_3.3.0
## [15] pkgconfig_2.0.3 Matrix_1.7-4
## [17] data.table_1.17.8 homologene_1.4.68.19.3.27
## [19] ggplotify_0.1.3 RColorBrewer_1.1-3
## [21] S7_0.2.0 uuid_1.2-1
## [23] lifecycle_1.0.4 compiler_4.5.1
## [25] farver_2.1.2 treeio_1.33.0
## [27] carData_3.0-5 ggtree_3.99.0
## [29] gprofiler2_0.2.3 ggfun_0.2.0
## [31] htmltools_0.5.8.1 sass_0.4.10
## [33] yaml_2.3.10 lazyeval_0.2.2
## [35] plotly_4.11.0 Formula_1.2-5
## [37] pillar_1.11.1 car_3.1-3
## [39] ggpubr_0.6.1 jquerylib_0.1.4
## [41] tidyr_1.3.1 cachem_1.1.0
## [43] grr_0.9.5 abind_1.4-8
## [45] nlme_3.1-168 tidyselect_1.2.1
## [47] aplot_0.2.9 digest_0.6.37
## [49] dplyr_1.1.4 purrr_1.1.0
## [51] bookdown_0.44 fastmap_1.2.0
## [53] grid_4.5.1 cli_3.6.5
## [55] magrittr_2.0.4 patchwork_1.3.2
## [57] dichromat_2.0-0.1 broom_1.0.10
## [59] ape_5.8-1 scales_1.4.0
## [61] backports_1.5.0 rappdirs_0.3.3
## [63] httr_1.4.7 rmarkdown_2.30
## [65] ggsignif_0.6.4 evaluate_1.0.5
## [67] knitr_1.50 viridisLite_0.4.2
## [69] gridGraphics_0.5-1 rlang_1.1.6
## [71] ggiraph_0.9.1 Rcpp_1.1.0
## [73] glue_1.8.0 tidytree_0.4.6
## [75] BiocManager_1.30.26 jsonlite_2.0.0
## [77] R6_2.6.1 systemfonts_1.2.3
## [79] fs_1.6.6