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 4.2.0 RC (2022-04-21 r82226)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.4 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_1.5.4 BiocStyle_2.25.0
##
## 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_1.4.3
## [8] GenomeInfoDb_1.33.3
## [9] googleAuthR_2.0.0
## [10] GenomicFiles_1.33.1
## [11] tools_4.2.0
## [12] bslib_0.3.1
## [13] utf8_1.2.2
## [14] R6_2.5.1
## [15] DBI_1.1.2
## [16] BiocGenerics_0.43.0
## [17] tidyselect_1.1.2
## [18] prettyunits_1.1.1
## [19] bit_4.0.4
## [20] curl_4.3.2
## [21] compiler_4.2.0
## [22] cli_3.3.0
## [23] Biobase_2.57.1
## [24] xml2_1.3.3
## [25] DelayedArray_0.23.0
## [26] rtracklayer_1.57.0
## [27] bookdown_0.26
## [28] sass_0.4.1
## [29] rappdirs_0.3.3
## [30] stringr_1.4.0
## [31] digest_0.6.29
## [32] Rsamtools_2.13.2
## [33] rmarkdown_2.14
## [34] R.utils_2.11.0
## [35] XVector_0.37.0
## [36] BSgenome.Hsapiens.1000genomes.hs37d5_0.99.1
## [37] pkgconfig_2.0.3
## [38] htmltools_0.5.2
## [39] MatrixGenerics_1.9.0
## [40] highr_0.9
## [41] dbplyr_2.1.1
## [42] fastmap_1.1.0
## [43] BSgenome_1.65.1
## [44] rlang_1.0.2
## [45] RSQLite_2.2.14
## [46] jquerylib_0.1.4
## [47] BiocIO_1.7.1
## [48] generics_0.1.2
## [49] jsonlite_1.8.0
## [50] BiocParallel_1.31.4
## [51] dplyr_1.0.9
## [52] R.oo_1.24.0
## [53] VariantAnnotation_1.43.2
## [54] RCurl_1.98-1.6
## [55] magrittr_2.0.3
## [56] GenomeInfoDbData_1.2.8
## [57] Matrix_1.4-1
## [58] Rcpp_1.0.8.3
## [59] S4Vectors_0.35.0
## [60] fansi_1.0.3
## [61] lifecycle_1.0.1
## [62] R.methodsS3_1.8.1
## [63] stringi_1.7.6
## [64] yaml_2.3.5
## [65] SummarizedExperiment_1.27.1
## [66] zlibbioc_1.43.0
## [67] BiocFileCache_2.5.0
## [68] grid_4.2.0
## [69] blob_1.2.3
## [70] parallel_4.2.0
## [71] crayon_1.5.1
## [72] lattice_0.20-45
## [73] Biostrings_2.65.0
## [74] GenomicFeatures_1.49.4
## [75] hms_1.1.1
## [76] KEGGREST_1.37.0
## [77] seqminer_8.4
## [78] knitr_1.39
## [79] pillar_1.7.0
## [80] GenomicRanges_1.49.0
## [81] rjson_0.2.21
## [82] biomaRt_2.53.2
## [83] stats4_4.2.0
## [84] XML_3.99-0.9
## [85] glue_1.6.2
## [86] evaluate_0.15
## [87] SNPlocs.Hsapiens.dbSNP144.GRCh37_0.99.20
## [88] data.table_1.14.2
## [89] BiocManager_1.30.18
## [90] png_0.1-7
## [91] vctrs_0.4.1
## [92] purrr_0.3.4
## [93] assertthat_0.2.1
## [94] cachem_1.0.6
## [95] xfun_0.31
## [96] restfulr_0.0.13
## [97] gargle_1.2.0
## [98] tibble_3.1.7
## [99] GenomicAlignments_1.33.0
## [100] AnnotationDbi_1.59.1
## [101] memoise_2.0.1
## [102] IRanges_2.31.0
## [103] ellipsis_0.3.2