epicompare 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/epicompareOnce 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/epicompare<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/epicompareFinally, 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] EpiCompare_1.2.0 BiocStyle_2.26.0
##
## loaded via a namespace (and not attached):
## [1] utf8_1.2.2
## [2] tidyselect_1.2.0
## [3] htmlwidgets_1.5.4
## [4] RSQLite_2.2.18
## [5] AnnotationDbi_1.60.0
## [6] grid_4.2.1
## [7] BiocParallel_1.32.0
## [8] scatterpie_0.1.8
## [9] munsell_0.5.0
## [10] codetools_0.2-18
## [11] withr_2.5.0
## [12] colorspace_2.0-3
## [13] GOSemSim_2.24.0
## [14] Biobase_2.58.0
## [15] filelock_1.0.2
## [16] highr_0.9
## [17] knitr_1.40
## [18] stats4_4.2.1
## [19] DOSE_3.24.0
## [20] labeling_0.4.2
## [21] MatrixGenerics_1.10.0
## [22] GenomeInfoDbData_1.2.9
## [23] polyclip_1.10-4
## [24] seqPattern_1.30.0
## [25] bit64_4.0.5
## [26] farver_2.1.1
## [27] vctrs_0.5.0
## [28] treeio_1.22.0
## [29] generics_0.1.3
## [30] xfun_0.34
## [31] BiocFileCache_2.6.0
## [32] R6_2.5.1
## [33] GenomeInfoDb_1.34.0
## [34] graphlayouts_0.8.3
## [35] locfit_1.5-9.6
## [36] bitops_1.0-7
## [37] BRGenomics_1.10.0
## [38] cachem_1.0.6
## [39] fgsea_1.24.0
## [40] gridGraphics_0.5-1
## [41] DelayedArray_0.24.0
## [42] assertthat_0.2.1
## [43] promises_1.2.0.1
## [44] BiocIO_1.8.0
## [45] scales_1.2.1
## [46] ggraph_2.1.0
## [47] enrichplot_1.18.0
## [48] gtable_0.3.1
## [49] tidygraph_1.2.2
## [50] rlang_1.0.6
## [51] genefilter_1.80.0
## [52] splines_4.2.1
## [53] rtracklayer_1.58.0
## [54] lazyeval_0.2.2
## [55] impute_1.72.0
## [56] BiocManager_1.30.19
## [57] yaml_2.3.6
## [58] reshape2_1.4.4
## [59] GenomicFeatures_1.50.0
## [60] httpuv_1.6.6
## [61] qvalue_2.30.0
## [62] tools_4.2.1
## [63] bookdown_0.29
## [64] ggplotify_0.1.0
## [65] gridBase_0.4-7
## [66] ggplot2_3.3.6
## [67] ellipsis_0.3.2
## [68] gplots_3.1.3
## [69] jquerylib_0.1.4
## [70] RColorBrewer_1.1-3
## [71] BiocGenerics_0.44.0
## [72] Rcpp_1.0.9
## [73] plyr_1.8.7
## [74] progress_1.2.2
## [75] zlibbioc_1.44.0
## [76] purrr_0.3.5
## [77] RCurl_1.98-1.9
## [78] prettyunits_1.1.1
## [79] viridis_0.6.2
## [80] cowplot_1.1.1
## [81] S4Vectors_0.36.0
## [82] SummarizedExperiment_1.28.0
## [83] ggrepel_0.9.1
## [84] magrittr_2.0.3
## [85] magick_2.7.3
## [86] data.table_1.14.4
## [87] matrixStats_0.62.0
## [88] hms_1.1.2
## [89] patchwork_1.1.2
## [90] mime_0.12
## [91] evaluate_0.17
## [92] xtable_1.8-4
## [93] HDO.db_0.99.1
## [94] XML_3.99-0.12
## [95] IRanges_2.32.0
## [96] gridExtra_2.3
## [97] compiler_4.2.1
## [98] biomaRt_2.54.0
## [99] tibble_3.1.8
## [100] KernSmooth_2.23-20
## [101] crayon_1.5.2
## [102] shadowtext_0.1.2
## [103] htmltools_0.5.3
## [104] ggfun_0.0.7
## [105] later_1.3.0
## [106] tzdb_0.3.0
## [107] tidyr_1.2.1
## [108] geneplotter_1.76.0
## [109] aplot_0.1.8
## [110] DBI_1.1.3
## [111] tweenr_2.0.2
## [112] ChIPseeker_1.34.0
## [113] genomation_1.30.0
## [114] dbplyr_2.2.1
## [115] MASS_7.3-58.1
## [116] rappdirs_0.3.3
## [117] boot_1.3-28
## [118] Matrix_1.5-1
## [119] readr_2.1.3
## [120] cli_3.4.1
## [121] parallel_4.2.1
## [122] igraph_1.3.5
## [123] GenomicRanges_1.50.0
## [124] pkgconfig_2.0.3
## [125] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
## [126] GenomicAlignments_1.34.0
## [127] plotly_4.10.0
## [128] xml2_1.3.3
## [129] ggtree_3.6.0
## [130] annotate_1.76.0
## [131] bslib_0.4.0
## [132] XVector_0.38.0
## [133] yulab.utils_0.0.5
## [134] stringr_1.4.1
## [135] digest_0.6.30
## [136] Biostrings_2.66.0
## [137] rmarkdown_2.17
## [138] fastmatch_1.1-3
## [139] tidytree_0.4.1
## [140] restfulr_0.0.15
## [141] curl_4.3.3
## [142] shiny_1.7.3
## [143] Rsamtools_2.14.0
## [144] gtools_3.9.3
## [145] rjson_0.2.21
## [146] lifecycle_1.0.3
## [147] nlme_3.1-160
## [148] jsonlite_1.8.3
## [149] viridisLite_0.4.1
## [150] BSgenome_1.66.0
## [151] fansi_1.0.3
## [152] pillar_1.8.1
## [153] lattice_0.20-45
## [154] KEGGREST_1.38.0
## [155] fastmap_1.1.0
## [156] httr_1.4.4
## [157] plotrix_3.8-2
## [158] survival_3.4-0
## [159] GO.db_3.16.0
## [160] interactiveDisplayBase_1.36.0
## [161] glue_1.6.2
## [162] png_0.1-7
## [163] BiocVersion_3.16.0
## [164] bit_4.0.4
## [165] ggforce_0.4.1
## [166] stringi_1.7.8
## [167] sass_0.4.2
## [168] blob_1.2.3
## [169] DESeq2_1.38.0
## [170] AnnotationHub_3.6.0
## [171] caTools_1.18.2
## [172] memoise_2.0.1
## [173] dplyr_1.0.10
## [174] ape_5.6-2