mungesumstats 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/mungesumstatsOnce 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/mungesumstats<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/mungesumstatsFinally, 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 4.3.0 RC (2023-04-13 r84269)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.17-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_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
##
## time zone: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] MungeSumstats_1.8.0 BiocStyle_2.28.0
##
## loaded via a namespace (and not attached):
## [1] tidyselect_1.2.0
## [2] dplyr_1.1.2
## [3] blob_1.2.4
## [4] filelock_1.0.2
## [5] R.utils_2.12.2
## [6] Biostrings_2.68.0
## [7] bitops_1.0-7
## [8] fastmap_1.1.1
## [9] RCurl_1.98-1.12
## [10] BiocFileCache_2.8.0
## [11] VariantAnnotation_1.46.0
## [12] GenomicAlignments_1.36.0
## [13] XML_3.99-0.14
## [14] digest_0.6.31
## [15] lifecycle_1.0.3
## [16] KEGGREST_1.40.0
## [17] RSQLite_2.3.1
## [18] googleAuthR_2.0.1
## [19] magrittr_2.0.3
## [20] compiler_4.3.0
## [21] rlang_1.1.0
## [22] sass_0.4.5
## [23] progress_1.2.2
## [24] tools_4.3.0
## [25] utf8_1.2.3
## [26] yaml_2.3.7
## [27] data.table_1.14.8
## [28] rtracklayer_1.60.0
## [29] knitr_1.42
## [30] prettyunits_1.1.1
## [31] bit_4.0.5
## [32] curl_5.0.0
## [33] DelayedArray_0.26.0
## [34] xml2_1.3.3
## [35] BiocParallel_1.34.0
## [36] BiocGenerics_0.46.0
## [37] R.oo_1.25.0
## [38] grid_4.3.0
## [39] stats4_4.3.0
## [40] fansi_1.0.4
## [41] biomaRt_2.56.0
## [42] SummarizedExperiment_1.30.0
## [43] cli_3.6.1
## [44] rmarkdown_2.21
## [45] crayon_1.5.2
## [46] generics_0.1.3
## [47] BSgenome.Hsapiens.1000genomes.hs37d5_0.99.1
## [48] httr_1.4.5
## [49] rjson_0.2.21
## [50] DBI_1.1.3
## [51] cachem_1.0.7
## [52] stringr_1.5.0
## [53] zlibbioc_1.46.0
## [54] assertthat_0.2.1
## [55] parallel_4.3.0
## [56] AnnotationDbi_1.62.0
## [57] BiocManager_1.30.20
## [58] XVector_0.40.0
## [59] restfulr_0.0.15
## [60] matrixStats_0.63.0
## [61] vctrs_0.6.2
## [62] Matrix_1.5-4
## [63] jsonlite_1.8.4
## [64] bookdown_0.33
## [65] IRanges_2.34.0
## [66] hms_1.1.3
## [67] S4Vectors_0.38.0
## [68] bit64_4.0.5
## [69] GenomicFiles_1.36.0
## [70] GenomicFeatures_1.52.0
## [71] jquerylib_0.1.4
## [72] glue_1.6.2
## [73] codetools_0.2-19
## [74] stringi_1.7.12
## [75] GenomeInfoDb_1.36.0
## [76] BiocIO_1.10.0
## [77] GenomicRanges_1.52.0
## [78] tibble_3.2.1
## [79] pillar_1.9.0
## [80] SNPlocs.Hsapiens.dbSNP155.GRCh37_0.99.24
## [81] rappdirs_0.3.3
## [82] htmltools_0.5.5
## [83] GenomeInfoDbData_1.2.10
## [84] BSgenome_1.68.0
## [85] R6_2.5.1
## [86] dbplyr_2.3.2
## [87] evaluate_0.20
## [88] lattice_0.21-8
## [89] Biobase_2.60.0
## [90] R.methodsS3_1.8.2
## [91] png_0.1-8
## [92] Rsamtools_2.16.0
## [93] gargle_1.4.0
## [94] memoise_2.0.1
## [95] bslib_0.4.2
## [96] xfun_0.39
## [97] fs_1.6.2
## [98] MatrixGenerics_1.12.0
## [99] pkgconfig_2.0.3