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 4.2.1 (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-3.16-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.16-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] MungeSumstats_1.6.0 BiocStyle_2.26.0
##
## loaded via a namespace (and not attached):
## [1] fs_1.5.2
## [2] bitops_1.0-7
## [3] matrixStats_0.62.0
## [4] bit64_4.0.5
## [5] filelock_1.0.2
## [6] progress_1.2.2
## [7] httr_1.4.4
## [8] GenomeInfoDb_1.34.0
## [9] googleAuthR_2.0.0
## [10] GenomicFiles_1.34.0
## [11] tools_4.2.1
## [12] bslib_0.4.0
## [13] utf8_1.2.2
## [14] R6_2.5.1
## [15] DBI_1.1.3
## [16] BiocGenerics_0.44.0
## [17] tidyselect_1.2.0
## [18] prettyunits_1.1.1
## [19] bit_4.0.4
## [20] curl_4.3.3
## [21] compiler_4.2.1
## [22] cli_3.4.1
## [23] Biobase_2.58.0
## [24] xml2_1.3.3
## [25] DelayedArray_0.24.0
## [26] rtracklayer_1.58.0
## [27] bookdown_0.29
## [28] sass_0.4.2
## [29] rappdirs_0.3.3
## [30] stringr_1.4.1
## [31] digest_0.6.30
## [32] Rsamtools_2.14.0
## [33] rmarkdown_2.17
## [34] R.utils_2.12.1
## [35] XVector_0.38.0
## [36] BSgenome.Hsapiens.1000genomes.hs37d5_0.99.1
## [37] pkgconfig_2.0.3
## [38] htmltools_0.5.3
## [39] MatrixGenerics_1.10.0
## [40] highr_0.9
## [41] dbplyr_2.2.1
## [42] fastmap_1.1.0
## [43] BSgenome_1.66.0
## [44] rlang_1.0.6
## [45] RSQLite_2.2.18
## [46] jquerylib_0.1.4
## [47] BiocIO_1.8.0
## [48] generics_0.1.3
## [49] jsonlite_1.8.3
## [50] BiocParallel_1.32.0
## [51] dplyr_1.0.10
## [52] R.oo_1.25.0
## [53] VariantAnnotation_1.44.0
## [54] RCurl_1.98-1.9
## [55] magrittr_2.0.3
## [56] GenomeInfoDbData_1.2.9
## [57] Matrix_1.5-1
## [58] Rcpp_1.0.9
## [59] S4Vectors_0.36.0
## [60] fansi_1.0.3
## [61] lifecycle_1.0.3
## [62] R.methodsS3_1.8.2
## [63] stringi_1.7.8
## [64] yaml_2.3.6
## [65] SummarizedExperiment_1.28.0
## [66] zlibbioc_1.44.0
## [67] BiocFileCache_2.6.0
## [68] grid_4.2.1
## [69] blob_1.2.3
## [70] parallel_4.2.1
## [71] crayon_1.5.2
## [72] lattice_0.20-45
## [73] Biostrings_2.66.0
## [74] GenomicFeatures_1.50.0
## [75] hms_1.1.2
## [76] KEGGREST_1.38.0
## [77] knitr_1.40
## [78] pillar_1.8.1
## [79] GenomicRanges_1.50.0
## [80] rjson_0.2.21
## [81] SNPlocs.Hsapiens.dbSNP155.GRCh37_0.99.22
## [82] codetools_0.2-18
## [83] biomaRt_2.54.0
## [84] stats4_4.2.1
## [85] XML_3.99-0.12
## [86] glue_1.6.2
## [87] evaluate_0.17
## [88] data.table_1.14.4
## [89] BiocManager_1.30.19
## [90] png_0.1-7
## [91] vctrs_0.5.0
## [92] assertthat_0.2.1
## [93] cachem_1.0.6
## [94] xfun_0.34
## [95] restfulr_0.0.15
## [96] gargle_1.2.1
## [97] tibble_3.1.8
## [98] GenomicAlignments_1.34.0
## [99] AnnotationDbi_1.60.0
## [100] memoise_2.0.1
## [101] IRanges_2.32.0
## [102] ellipsis_0.3.2