hihg-um / docker-r

R build in docker
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Can you also add these 2 libraries to genesis?  GWASdata  BiocParallel #45

Open thebigcorporation opened 2 months ago

thebigcorporation commented 2 months ago

The BiocParallel package is provided by Ubuntu, and the GWASdata package has to be built

thebigcorporation commented 2 months ago

This is fixed by: https://github.com/hihg-um/docker-r/pull/44

sven@aws:/scratch/sven/checkout/hihg_um/docker/docker-r$ make docker_test

Testing Docker container: hihg-um/genesis:gwasdata-0-g4ed05ca-dirty Loading required package: GWASTools Loading required package: Biobase Loading required package: BiocGenerics

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:stats':

IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
tapply, union, unique, unsplit, which.max, which.min

Welcome to Bioconductor

Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.

R version 4.3.3 (2024-02-29) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 24.04 LTS

Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.12.0 LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0

locale: [1] C

time zone: UTC tzcode source: system (glibc)

attached base packages: [1] stats graphics grDevices utils datasets methods base

other attached packages: [1] GENESIS_2.35.0 BiocParallel_1.36.0 GWASdata_1.40.0 [4] GWASTools_1.48.0 Biobase_2.62.0 BiocGenerics_0.48.1

loaded via a namespace (and not attached): [1] tidyselect_1.2.1 dplyr_1.1.4 blob_1.2.4 [4] Biostrings_2.70.3 bitops_1.0-7 gdsfmt_1.38.0 [7] fastmap_1.2.0 RCurl_1.98-1.14 rpart_4.1.23 [10] lifecycle_1.0.4 survival_3.5-8 RSQLite_2.3.7 [13] magrittr_2.0.3 compiler_4.3.3 rlang_1.1.4 [16] tools_4.3.3 utf8_1.2.4 SNPRelate_1.36.1 [19] data.table_1.15.4 bit_4.0.5 SeqArray_1.42.4 [22] purrr_1.0.2 GWASExactHW_1.2 nnet_7.3-19 [25] grid_4.3.3 stats4_4.3.3 fansi_1.0.6 [28] jomo_2.7-6 mice_3.16.0 iterators_1.0.14 [31] MASS_7.3-60.0.1 cli_3.6.3 crayon_1.5.3 [34] generics_0.1.3 minqa_1.2.7 DBI_1.2.3 [37] DNAcopy_1.76.0 cachem_1.1.0 zlibbioc_1.48.2 [40] operator.tools_1.6.3 splines_4.3.3 parallel_4.3.3 [43] XVector_0.42.0 vctrs_0.6.5 boot_1.3-30 [46] glmnet_4.1-8 Matrix_1.6-5 sandwich_3.1-0 [49] SparseM_1.84 IRanges_2.36.0 S4Vectors_0.40.2 [52] quantsmooth_1.68.0 bit64_4.0.5 mitml_0.4-5 [55] foreach_1.5.2 tidyr_1.3.1 glue_1.7.0 [58] nloptr_2.1.1 pan_1.9 codetools_0.2-19 [61] shape_1.4.6.1 GenomeInfoDb_1.38.8 GenomicRanges_1.54.1 [64] lmtest_0.9-40 lme4_1.1-35.4 tibble_3.2.1 [67] pillar_1.9.0 quantreg_5.98 GenomeInfoDbData_1.2.11 [70] R6_2.5.1 SeqVarTools_1.40.0 formula.tools_1.7.1 [73] lattice_0.22-5 backports_1.5.0 memoise_2.0.1 [76] broom_1.0.6 MatrixModels_0.5-3 Rcpp_1.0.12 [79] nlme_3.1-164 mgcv_1.9-1 logistf_1.26.0 [82] zoo_1.8-12 pkgconfig_2.0.3