vignettes/docker.Rmd
docker.RmdMAGMA.Celltyping 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/MAGMA.CelltypingOnce 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/MAGMA.Celltyping<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/MAGMA.CelltypingFor 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 4.4.1 (2024-06-14)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.5 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-r0.3.20.so; LAPACK version 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: UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] MAGMA.Celltyping_2.0.14 BiocStyle_2.33.1
##
## loaded via a namespace (and not attached):
## [1] splines_4.4.1 BiocIO_1.15.2
## [3] bitops_1.0-9 ggplotify_0.1.2
## [5] filelock_1.0.3 tibble_3.2.1
## [7] R.oo_1.26.0 XML_3.99-0.17
## [9] lifecycle_1.0.4 rstatix_0.7.2
## [11] lattice_0.22-6 MASS_7.3-61
## [13] backports_1.5.0 magrittr_2.0.3
## [15] limma_3.61.12 plotly_4.10.4
## [17] sass_0.4.9 rmarkdown_2.28
## [19] jquerylib_0.1.4 yaml_2.3.10
## [21] HGNChelper_0.8.14 minqa_1.2.8
## [23] DBI_1.2.3 abind_1.4-8
## [25] zlibbioc_1.51.1 GenomicRanges_1.57.1
## [27] purrr_1.0.2 R.utils_2.12.3
## [29] BiocGenerics_0.51.3 RCurl_1.98-1.16
## [31] yulab.utils_0.1.7 VariantAnnotation_1.51.1
## [33] rappdirs_0.3.3 GenomeInfoDbData_1.2.13
## [35] IRanges_2.39.2 S4Vectors_0.43.2
## [37] tidytree_0.4.6 pkgdown_2.1.1
## [39] codetools_0.2-20 DelayedArray_0.31.13
## [41] tidyselect_1.2.1 aplot_0.2.3
## [43] UCSC.utils_1.1.0 farver_2.1.2
## [45] lme4_1.1-35.5 matrixStats_1.4.1
## [47] stats4_4.4.1 BiocFileCache_2.13.0
## [49] GenomicAlignments_1.41.0 jsonlite_1.8.9
## [51] Formula_1.2-5 systemfonts_1.1.0
## [53] tools_4.4.1 treeio_1.29.1
## [55] ragg_1.3.3 Rcpp_1.0.13
## [57] glue_1.8.0 SparseArray_1.5.41
## [59] xfun_0.48 MatrixGenerics_1.17.0
## [61] GenomeInfoDb_1.41.2 RNOmni_1.0.1.2
## [63] dplyr_1.1.4 BiocManager_1.30.25
## [65] fastmap_1.2.0 boot_1.3-31
## [67] fansi_1.0.6 digest_0.6.37
## [69] R6_2.5.1 gridGraphics_0.5-1
## [71] textshaping_0.4.0 colorspace_2.1-1
## [73] RSQLite_2.3.7 R.methodsS3_1.8.2
## [75] utf8_1.2.4 tidyr_1.3.1
## [77] generics_0.1.3 data.table_1.16.0
## [79] rtracklayer_1.65.0 httr_1.4.7
## [81] htmlwidgets_1.6.4 S4Arrays_1.5.10
## [83] pkgconfig_2.0.3 gtable_0.3.5
## [85] blob_1.2.4 SingleCellExperiment_1.27.2
## [87] XVector_0.45.0 htmltools_0.5.8.1
## [89] carData_3.0-5 bookdown_0.40
## [91] scales_1.3.0 Biobase_2.65.1
## [93] png_0.1-8 ggfun_0.1.6
## [95] ggdendro_0.2.0 knitr_1.48
## [97] reshape2_1.4.4 rjson_0.2.23
## [99] nloptr_2.1.1 nlme_3.1-166
## [101] curl_5.2.3 cachem_1.1.0
## [103] stringr_1.5.1 BiocVersion_3.20.0
## [105] parallel_4.4.1 AnnotationDbi_1.67.0
## [107] restfulr_0.0.15 desc_1.4.3
## [109] pillar_1.9.0 grid_4.4.1
## [111] vctrs_0.6.5 ggpubr_0.6.0
## [113] car_3.1-3 dbplyr_2.5.0
## [115] evaluate_1.0.0 orthogene_1.11.0
## [117] GenomicFeatures_1.57.1 cli_3.6.3
## [119] compiler_4.4.1 Rsamtools_2.21.2
## [121] rlang_1.1.4 crayon_1.5.3
## [123] grr_0.9.5 ggsignif_0.6.4
## [125] gprofiler2_0.2.3 EWCE_1.13.1
## [127] plyr_1.8.9 fs_1.6.4
## [129] stringi_1.8.4 viridisLite_0.4.2
## [131] ewceData_1.13.0 BiocParallel_1.39.0
## [133] assertthat_0.2.1 babelgene_22.9
## [135] munsell_0.5.1 Biostrings_2.73.2
## [137] lazyeval_0.2.2 gh_1.4.1
## [139] homologene_1.4.68.19.3.27 Matrix_1.7-0
## [141] ExperimentHub_2.13.1 MungeSumstats_1.13.7
## [143] BSgenome_1.73.1 patchwork_1.3.0
## [145] bit64_4.5.2 ggplot2_3.5.1
## [147] KEGGREST_1.45.1 statmod_1.5.0
## [149] SummarizedExperiment_1.35.3 AnnotationHub_3.13.3
## [151] googleAuthR_2.0.2 gargle_1.5.2
## [153] broom_1.0.7 memoise_2.0.1
## [155] bslib_0.8.0 ggtree_3.13.1
## [157] bit_4.5.0 splitstackshape_1.4.8
## [159] ape_5.8