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/orthogeneOnce 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/orthogeneFinally, 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.
## R version 4.4.2 (2024-10-31)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.1 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-r0.3.26.so; LAPACK version 3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 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: Etc/UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] orthogene_1.13.0 BiocStyle_2.35.0
##
## loaded via a namespace (and not attached):
## [1] gtable_0.3.6 babelgene_22.9
## [3] xfun_0.50 bslib_0.8.0
## [5] ggplot2_3.5.1 htmlwidgets_1.6.4
## [7] rstatix_0.7.2 lattice_0.22-6
## [9] vctrs_0.6.5 tools_4.4.2
## [11] generics_0.1.3 yulab.utils_0.1.9
## [13] parallel_4.4.2 tibble_3.2.1
## [15] pkgconfig_2.0.3 Matrix_1.7-2
## [17] data.table_1.16.4 homologene_1.4.68.19.3.27
## [19] ggplotify_0.1.2 lifecycle_1.0.4
## [21] compiler_4.4.2 farver_2.1.2
## [23] treeio_1.31.0 munsell_0.5.1
## [25] carData_3.0-5 ggtree_3.15.0
## [27] ggfun_0.1.8 gprofiler2_0.2.3
## [29] htmltools_0.5.8.1 sys_3.4.3
## [31] buildtools_1.0.0 sass_0.4.9
## [33] yaml_2.3.10 lazyeval_0.2.2
## [35] plotly_4.10.4 Formula_1.2-5
## [37] pillar_1.10.1 car_3.1-3
## [39] ggpubr_0.6.0 jquerylib_0.1.4
## [41] tidyr_1.3.1 cachem_1.1.0
## [43] grr_0.9.5 abind_1.4-8
## [45] nlme_3.1-167 tidyselect_1.2.1
## [47] aplot_0.2.4 digest_0.6.37
## [49] dplyr_1.1.4 purrr_1.0.2
## [51] maketools_1.3.1 fastmap_1.2.0
## [53] grid_4.4.2 colorspace_2.1-1
## [55] cli_3.6.3 magrittr_2.0.3
## [57] patchwork_1.3.0 broom_1.0.7
## [59] ape_5.8-1 scales_1.3.0
## [61] backports_1.5.0 httr_1.4.7
## [63] rmarkdown_2.29 ggsignif_0.6.4
## [65] evaluate_1.0.3 knitr_1.49
## [67] viridisLite_0.4.2 gridGraphics_0.5-1
## [69] rlang_1.1.5 Rcpp_1.0.14
## [71] glue_1.8.0 tidytree_0.4.6
## [73] BiocManager_1.30.25 jsonlite_1.8.9
## [75] R6_2.5.1 fs_1.6.5