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 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.5 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_1.2.1 BiocStyle_2.24.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.9 ape_5.6-2
## [3] lattice_0.20-45 tidyr_1.2.1
## [5] assertthat_0.2.1 digest_0.6.29
## [7] utf8_1.2.2 R6_2.5.1
## [9] backports_1.4.1 evaluate_0.16
## [11] httr_1.4.4 ggplot2_3.3.6
## [13] pillar_1.8.1 ggfun_0.0.7
## [15] yulab.utils_0.0.5 rlang_1.0.6
## [17] lazyeval_0.2.2 data.table_1.14.2
## [19] car_3.1-0 jquerylib_0.1.4
## [21] Matrix_1.5-1 rmarkdown_2.16
## [23] stringr_1.4.1 htmlwidgets_1.5.4
## [25] munsell_0.5.0 broom_1.0.1
## [27] gprofiler2_0.2.1 compiler_4.2.1
## [29] xfun_0.33 pkgconfig_2.0.3
## [31] gridGraphics_0.5-1 htmltools_0.5.3
## [33] tidyselect_1.1.2 tibble_3.1.8
## [35] bookdown_0.29 viridisLite_0.4.1
## [37] fansi_1.0.3 dplyr_1.0.10
## [39] ggpubr_0.4.0 grid_4.2.1
## [41] nlme_3.1-159 jsonlite_1.8.2
## [43] gtable_0.3.1 lifecycle_1.0.2
## [45] DBI_1.1.3 magrittr_2.0.3
## [47] scales_1.2.1 tidytree_0.4.1
## [49] cli_3.4.1 stringi_1.7.8
## [51] cachem_1.0.6 carData_3.0-5
## [53] ggsignif_0.6.3 ggtree_3.4.4
## [55] bslib_0.4.0 generics_0.1.3
## [57] vctrs_0.4.2 treeio_1.20.2
## [59] tools_4.2.1 homologene_1.4.68.19.3.27
## [61] ggplotify_0.1.0 glue_1.6.2
## [63] purrr_0.3.4 abind_1.4-5
## [65] parallel_4.2.1 fastmap_1.1.0
## [67] yaml_2.3.5 babelgene_22.9
## [69] colorspace_2.0-3 BiocManager_1.30.18
## [71] rstatix_0.7.0 aplot_0.1.7
## [73] plotly_4.10.0 knitr_1.40
## [75] patchwork_1.1.2 sass_0.4.2