[Bioc-devel] Unable to reproduce OS/X build error for "netDx" package
Shraddha Pai
@hr@ddh@p@|@neuro @end|ng |rom gm@||@com
Wed Jun 24 18:09:51 CEST 2020
Hi BioC community,
My package relies on a Java jar and detects whether the OS has Java 8 or
11, to be accordingly compatible. I can't seem to resolve the build error
on the BioC Mac system; the error message is a symptom of Java 8
incompatibility.
However, on my 2014 Mac Air which runs Java 8, the offending example
("Predict_CaseControl_from_CNV.Rmd") runs through to completion. What is
the issue here? It would be great to have all operating systems building
successfully.
Details below. Thanks!
Shraddha
---
Error: This is the error: "WARNING: An illegal reflective access operation
has occurred
WARNING: Illegal reflective access by net.sf.cglib.core.ReflectUtils$2
(file:/Users/biocbuild/Library/Caches/netDx/763502120e4_genemania-netdx.jar)
to method java.lang.ClassLoader.defineClass(java.lang.String,byte[],int,int,java.security.ProtectionDomain)
WARNING: Please consider reporting this to the maintainers of
net.sf.cglib.core.ReflectUtils$2"
Mac specs: MacBook Air early 2014; High Sierra 10.13.6
"java -version" output:
java version "1.8.0_31"
Java(TM) SE Runtime Environment (build 1.8.0_31-b13)
Java HotSpot(TM) 64-Bit Server VM (build 25.31-b07, mixed mode)
R: 4.0.2 ; BioC 3.11
sessionInfo output:
> sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS High Sierra 10.13.6
Matrix products: default
BLAS:
/Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK:
/Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
locale:
[1] C/C/C/C/C/en_CA.UTF-8
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] BiocFileCache_1.12.0 dbplyr_1.4.4 GenomicRanges_1.40.0
[4] GenomeInfoDb_1.24.2 IRanges_2.22.2 S4Vectors_0.26.1
[7] BiocGenerics_0.34.0 netDx_1.1.1 BiocStyle_2.16.0
loaded via a namespace (and not attached):
[1] Biobase_2.48.0 httr_1.4.1
[3] splines_4.0.2 bit64_0.9-7
[5] foreach_1.5.0 R.utils_2.9.2
[7] assertthat_0.2.1 BiocManager_1.30.10
[9] blob_1.2.1 GenomeInfoDbData_1.2.3
[11] yaml_2.2.1 pillar_1.4.4
[13] RSQLite_2.2.0 lattice_0.20-41
[15] glue_1.4.1 digest_0.6.25
[17] RColorBrewer_1.1-2 XVector_0.28.0
[19] colorspace_1.4-1 plyr_1.8.6
[21] htmltools_0.5.0 Matrix_1.2-18
[23] R.oo_1.23.0 XML_3.99-0.3
[25] pkgconfig_2.0.3 bookdown_0.20
[27] zlibbioc_1.34.0 purrr_0.3.4
[29] scales_1.1.1 MultiAssayExperiment_1.14.0
[31] pracma_2.2.9 combinat_0.0-8
[33] tibble_3.0.1 generics_0.0.2
[35] ggplot2_3.3.2 ellipsis_0.3.1
[37] SummarizedExperiment_1.18.1 ROCR_1.0-11
[39] survival_3.1-12 RJSONIO_1.3-1.4
[41] magrittr_1.5 crayon_1.3.4
[43] memoise_1.1.0 evaluate_0.14
[45] R.methodsS3_1.8.0 doParallel_1.0.15
[47] graph_1.66.0 tools_4.0.2
[49] lifecycle_0.2.0 matrixStats_0.56.0
[51] stringr_1.4.0 glmnet_4.0-2
[53] munsell_0.5.0 DelayedArray_0.14.0
[55] compiler_4.0.2 rlang_0.4.6
[57] grid_4.0.2 RCurl_1.98-1.2
[59] iterators_1.0.12 rappdirs_0.3.1
[61] bigmemory.sri_0.1.3 igraph_1.2.5
[63] bitops_1.0-6 rmarkdown_2.3
[65] gtable_0.3.0 codetools_0.2-16
[67] RCy3_2.8.0 DBI_1.1.0
[69] curl_4.3 reshape2_1.4.4
[71] bigmemory_4.5.36 R6_2.4.1
[73] knitr_1.29 dplyr_1.0.0
[75] bit_1.1-15.2 shape_1.4.4
[77] stringi_1.4.6 Rcpp_1.0.4.6
[79] vctrs_0.3.1 tidyselect_1.1.0
[81] xfun_0.15
--
Shraddha Pai, PhD
http://shraddhapai.com ; @spaiglass on Twitter
Post-doctoral Fellow, http://baderlab.org
The Donnelly Centre for Cellular and Biomolecular Research
University of Toronto
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