orthogene 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/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 8787:8787 \
neurogenomicslab/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://neurogenomicslab/orthogene
Finally, 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 beta (2024-04-15 r86425)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.19-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_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: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] orthogene_1.10.0 BiocStyle_2.32.0
##
## loaded via a namespace (and not attached):
## [1] gtable_0.3.5 babelgene_22.9
## [3] xfun_0.43 bslib_0.7.0
## [5] ggplot2_3.5.1 htmlwidgets_1.6.4
## [7] rstatix_0.7.2 lattice_0.22-6
## [9] vctrs_0.6.5 tools_4.4.0
## [11] generics_0.1.3 yulab.utils_0.1.4
## [13] parallel_4.4.0 tibble_3.2.1
## [15] fansi_1.0.6 pkgconfig_2.0.3
## [17] Matrix_1.7-0 data.table_1.15.4
## [19] homologene_1.4.68.19.3.27 ggplotify_0.1.2
## [21] lifecycle_1.0.4 compiler_4.4.0
## [23] treeio_1.28.0 munsell_0.5.1
## [25] carData_3.0-5 ggtree_3.12.0
## [27] ggfun_0.1.4 gprofiler2_0.2.3
## [29] htmltools_0.5.8.1 sass_0.4.9
## [31] yaml_2.3.8 lazyeval_0.2.2
## [33] plotly_4.10.4 pillar_1.9.0
## [35] car_3.1-2 ggpubr_0.6.0
## [37] jquerylib_0.1.4 tidyr_1.3.1
## [39] cachem_1.0.8 grr_0.9.5
## [41] abind_1.4-5 nlme_3.1-164
## [43] tidyselect_1.2.1 aplot_0.2.2
## [45] digest_0.6.35 dplyr_1.1.4
## [47] purrr_1.0.2 bookdown_0.39
## [49] fastmap_1.1.1 grid_4.4.0
## [51] colorspace_2.1-0 cli_3.6.2
## [53] magrittr_2.0.3 patchwork_1.2.0
## [55] utf8_1.2.4 broom_1.0.5
## [57] ape_5.8 scales_1.3.0
## [59] backports_1.4.1 httr_1.4.7
## [61] rmarkdown_2.26 ggsignif_0.6.4
## [63] memoise_2.0.1 evaluate_0.23
## [65] knitr_1.46 viridisLite_0.4.2
## [67] gridGraphics_0.5-1 rlang_1.1.3
## [69] Rcpp_1.0.12 glue_1.7.0
## [71] tidytree_0.4.6 BiocManager_1.30.22
## [73] jsonlite_1.8.8 R6_2.5.1
## [75] fs_1.6.4