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 4.2.0 RC (2022-04-19 r82224)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.15-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.15-bioc/R/lib/libRlapack.so
##
## 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
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] orthogene_1.2.0 BiocStyle_2.24.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.8.3 ape_5.6-2
## [3] lattice_0.20-45 tidyr_1.2.0
## [5] assertthat_0.2.1 digest_0.6.29
## [7] utf8_1.2.2 R6_2.5.1
## [9] backports_1.4.1 evaluate_0.15
## [11] httr_1.4.2 ggplot2_3.3.5
## [13] pillar_1.7.0 ggfun_0.0.6
## [15] yulab.utils_0.0.4 rlang_1.0.2
## [17] lazyeval_0.2.2 data.table_1.14.2
## [19] car_3.0-12 jquerylib_0.1.4
## [21] Matrix_1.4-1 rmarkdown_2.14
## [23] stringr_1.4.0 htmlwidgets_1.5.4
## [25] munsell_0.5.0 broom_0.8.0
## [27] gprofiler2_0.2.1 compiler_4.2.0
## [29] xfun_0.30 pkgconfig_2.0.3
## [31] gridGraphics_0.5-1 htmltools_0.5.2
## [33] tidyselect_1.1.2 tibble_3.1.6
## [35] bookdown_0.26 viridisLite_0.4.0
## [37] fansi_1.0.3 crayon_1.5.1
## [39] dplyr_1.0.8 ggpubr_0.4.0
## [41] grid_4.2.0 nlme_3.1-157
## [43] jsonlite_1.8.0 gtable_0.3.0
## [45] lifecycle_1.0.1 DBI_1.1.2
## [47] magrittr_2.0.3 scales_1.2.0
## [49] tidytree_0.3.9 cli_3.3.0
## [51] stringi_1.7.6 carData_3.0-5
## [53] ggsignif_0.6.3 ggtree_3.4.0
## [55] bslib_0.3.1 ellipsis_0.3.2
## [57] generics_0.1.2 vctrs_0.4.1
## [59] treeio_1.20.0 tools_4.2.0
## [61] homologene_1.4.68.19.3.27 ggplotify_0.1.0
## [63] glue_1.6.2 purrr_0.3.4
## [65] abind_1.4-5 parallel_4.2.0
## [67] fastmap_1.1.0 yaml_2.3.5
## [69] babelgene_22.3 colorspace_2.0-3
## [71] BiocManager_1.30.17 rstatix_0.7.0
## [73] aplot_0.1.3 plotly_4.10.0
## [75] knitr_1.38 patchwork_1.1.1
## [77] sass_0.4.1