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IntOMICS
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- Repository: https://github.com/anna-pacinkova/IntOMICS
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Hi @anna-pacinkova
Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.
The DESCRIPTION file for this package is:
Package: IntOMICS
Type: Package
Title: Integrative analysis of multi-omics data to infer regulatory networks
Version: 0.99.0
Authors@R: person("Pacinkova", "Anna", email = "[email protected]", role = c("cre","aut"))
URL: https://gitlab.ics.muni.cz/bias/intomics_package
Description: IntOMICS is an efficient integrative framework based on Bayesian networks. IntOMICS systematically analyses gene expression (GE), DNA methylation (METH), copy number variation (CNV) and biological prior knowledge (B) to infer regulatory networks. IntOMICS complements the missing biological prior knowledge by so-called empirical biological knowledge (empB), estimated from the available experimental data. An automatically tuned MCMC algorithm (Yang and Rosenthal, 2017) estimates model parameters and the empirical biological knowledge. Conventional MCMC algorithm with additional Markov blanket resampling (MBR) step (Su and Borsuk, 2016) infers resulting regulatory network structure consisting of three types of nodes: GE nodes refer to gene expression levels, CNV nodes refer to associated copy number variations, and METH nodes refer to associated DNA methylation probe(s).
Depends: R (>= 4.2.0)
Imports: bnlearn, bnstruct, matrixStats, RColorBrewer, bestNormalize, igraph, gplots, stats, utils, graphics, grDevices, numbers
License: GPL-3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
VignetteBuilder: knitr
RoxygenNote: 7.2.0
LazyData: false
Suggests: rmarkdown, knitr, ggraph
biocViews: Software, DNAMethylation, GeneExpression, CopyNumberVariation, SystemsBiology, GeneRegulation, Network, Bayesian
Thank you for this very interesting submission. I am concerned that the building of the vignette seems to take a very long time. I have seen
and this approach to organizing the data should be improved. The curatedTCGAData package uses MultiAssayExperiments for this type of data and indeed the COAD data. You should consider using it and not duplicating the content in your package. The use of ENTREZID:nnnn for feature labeling is unusual, please have a look at how this is handled in curatedTCGAData.
11 days have passed, please indicate your intentions with this package. Thank you
Dear Vince,
I am sorry for the delay, I absoluteley missed the previous email. I will check your recommendations asap.
Kind regards, Anna
Dne so 20. 8. 2022 12:03 uživatel Vince Carey @.***> napsal:
11 days have passed, please indicate your intentions with this package. Thank you
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Dear Vince,
FYI, I am working on the IntOMICS package modifications. I am still blocked with the MultiAssayExperiment, because there are missing rownames in COAD GISTIC assay. This is just a friendly reminder that I am working on it.
Best wishes, Anna
so 20. 8. 2022 v 15:49 odesílatel Anna Pačínková @.***> napsal:
Dear Vince,
I am sorry for the delay, I absoluteley missed the previous email. I will check your recommendations asap.
Kind regards, Anna
Dne so 20. 8. 2022 12:03 uživatel Vince Carey @.***> napsal:
11 days have passed, please indicate your intentions with this package. Thank you
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Hi,
I am trying to download COAD RNAseq, Methylation and CNV data (summarized for genes) and for CNV data I get empty rownames. The same happens with READ samples.
library(curatedTCGAData) library(MultiAssayExperiment) library(TCGAutils) coad_SE <- curatedTCGAData("COAD", c("RNASeq2GeneNorm_illuminahiseq","Methylation_methyl450","GISTIC_AllByGene"), version = "2.0.1", dry.run = FALSE)
I have empty rownames:
coad_SE[[1]] class: SummarizedExperiment dim: 24776 449 metadata(0): assays(1): '' rownames: NULL rowData names(3): Gene.Symbol Locus.ID Cytoband colnames(449): TCGA-3L-AA1B-01A-11D-A36W-01 TCGA-4N-A93T-01A-11D-A36W-01 ... TCGA-T9-A92H-01A-11D-A36W-01 TCGA-WS-AB45-01A-11D-A40O-01 colData names(0):
sessionInfo() R version 4.2.1 (2022-06-23) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 20.04.4 LTS
Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
locale: [1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C LC_TIME=cs_CZ.UTF-8 LC_COLLATE=en_AU.UTF-8 LC_MONETARY=cs_CZ.UTF-8 [6] LC_MESSAGES=en_AU.UTF-8 LC_PAPER=cs_CZ.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=cs_CZ.UTF-8 LC_IDENTIFICATION=C
attached base packages: [1] stats4 stats graphics grDevices utils datasets methods base
other attached packages: [1] HDF5Array_1.25.2 DelayedArray_0.23.1 Matrix_1.4-1 rhdf5_2.41.1 [5] curatedTCGAData_1.19.0 TCGAutils_1.17.2 MultiAssayExperiment_1.23.4 SummarizedExperiment_1.27.1 [9] Biobase_2.57.1 GenomicRanges_1.49.1 GenomeInfoDb_1.33.5 IRanges_2.31.2 [13] S4Vectors_0.35.1 BiocGenerics_0.43.1 MatrixGenerics_1.9.1 matrixStats_0.62.0
loaded via a namespace (and not attached): [1] bitops_1.0-7 bit64_4.0.5 filelock_1.0.2 progress_1.2.2 [5] httr_1.4.4 GenomicDataCommons_1.21.2 tools_4.2.1 utf8_1.2.2 [9] R6_2.5.1 DBI_1.1.3 rhdf5filters_1.9.0 tidyselect_1.1.2 [13] prettyunits_1.1.1 bit_4.0.4 curl_4.3.2 compiler_4.2.1 [17] cli_3.3.0 rvest_1.0.3 xml2_1.3.3 rtracklayer_1.57.0 [21] readr_2.1.2 rappdirs_0.3.3 stringr_1.4.1 digest_0.6.29 [25] Rsamtools_2.13.3 rmarkdown_2.15 XVector_0.37.0 pkgconfig_2.0.3 [29] htmltools_0.5.3 dbplyr_2.2.1 fastmap_1.1.0 rlang_1.0.4 [33] rstudioapi_0.13 RSQLite_2.2.16 shiny_1.7.2 BiocIO_1.7.1 [37] generics_0.1.3 jsonlite_1.8.0 BiocParallel_1.31.12 dplyr_1.0.9 [41] RCurl_1.98-1.8 magrittr_2.0.3 GenomeInfoDbData_1.2.8 Rhdf5lib_1.19.2 [45] Rcpp_1.0.9 fansi_1.0.3 lifecycle_1.0.1 stringi_1.7.8 [49] yaml_2.3.5 zlibbioc_1.43.0 BiocFileCache_2.5.0 AnnotationHub_3.5.0 [53] grid_4.2.1 blob_1.2.3 promises_1.2.0.1 parallel_4.2.1 [57] ExperimentHub_2.5.0 crayon_1.5.1 lattice_0.20-45 Biostrings_2.65.2 [61] GenomicFeatures_1.49.5 hms_1.1.2 KEGGREST_1.37.3 knitr_1.39 [65] pillar_1.8.1 rjson_0.2.21 codetools_0.2-18 biomaRt_2.53.2 [69] XML_3.99-0.10 glue_1.6.2 BiocVersion_3.16.0 evaluate_0.16 [73] BiocManager_1.30.18 httpuv_1.6.5 png_0.1-7 vctrs_0.4.1 [77] tzdb_0.3.0 purrr_0.3.4 assertthat_0.2.1 cachem_1.0.6 [81] xfun_0.32 mime_0.12 xtable_1.8-4 restfulr_0.0.15 [85] later_1.3.0 tibble_3.1.8 GenomicAlignments_1.33.1 AnnotationDbi_1.59.1 [89] memoise_2.0.1 ellipsis_0.3.2 interactiveDisplayBase_1.35.0
so 10. 9. 2022 v 16:50 odesílatel Vince Carey @.***> napsal:
@LiNk-NY https://github.com/LiNk-NY -- any thoughts about GISTIC for COAD? Missing rownames?
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Hi @vjcitn @anna-pacinkova
Every assay should have row names. I will take a closer look.
In the meantime, you can get row names from the rowData:
gabg <- x[["COAD_GISTIC_AllByGene-20160128"]]
rownames(gabg) <- rowData(gabg)[["Gene.Symbol"]]
Best, Marcel
Hello Vince,
I have changed the TCGA data input as you have suggested - now IntOMICS
vignette uses the curatedTCGA package to load an example dataset
consisting of gene expression, CNV and methylation data.
I have also changed the data organisation, gene symbols are used as the
primary gene IDs, entrez IDs are used for the network inference inside the
package.
For a faster check of the package, I have deleted examples in functions
that are not directly called by the user. Bayesian networks are time
expensive, so this is the reason why it takes a little bit longer...
All changes are pushed to the main GitHub repo.
Best wishes, Anna
po 12. 9. 2022 v 16:43 odesílatel Marcel Ramos @.***> napsal:
Hi @vjcitn https://github.com/vjcitn @anna-pacinkova https://github.com/anna-pacinkova Every assay should have row names. I will take a closer look. In the meantime, you can get row names from the rowData:
gabg <- x[["COAD_GISTIC_AllByGene-20160128"]] rownames(gabg) <- rowData(gabg)[["Gene.Symbol"]]
Best, Marcel
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Thanks for doing this. Before I plunge in, it seems to me you have library(curatedTCGAData) in your vignette but it is not declared as Suggests in the DESCRIPTION. Can you take care of this and any other recommendations from R CMD check or BiocCheck provide? It seems to me the vignette takes a long time to compile?
Thank you for the feedback. DESCRIPTION file was modified.
About the vignette: Is it possible that code chunks in mode 'eval=FALSE' are also tested during the R CMD check? Because when I knit the vignette on my laptop, it does not take too much time. However, the R CMD check is pretty long. As I said, the MCMC simulation of Bayesian networks takes some time. I saved the result from this function for the user so that it can be loaded into the current workspace. And calling longFormat function from curatedTCGA also takes some time.
Concerning the R CMD check and BiocCheck: There is still this "ERROR: At least 80% of man pages documenting exported objects must have runnable examples." because I removed the examples from functions that are not directly called by the end user. As I have mentioned before, these examples took a very long time to proceed because of MCMC simulation on Bayesian networks. Is it OK, or should I recover them?
Best, Anna
út 20. 9. 2022 v 22:09 odesílatel Vince Carey @.***> napsal:
Thanks for doing this. Before I plunge in, it seems to me you have library(curatedTCGAData) in your vignette but it is not declared as Suggests in the DESCRIPTION. Can you take care of this and any other recommendations from R CMD check or BiocCheck provide? It seems to me the vignette takes a long time to compile?
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Hi Anna, @anna-pacinkova
I would highly recommend looking into TCGAutils for working with data from curatedTCGAData.
I've done something similar to the data without the need to use longFormat. I recommend only using that function on data that does not contain both tumors and normals for efficiency (where replicate observations have been consolidated or removed). In this case using longFormat is not required AFAICT.
Something like this should get you the same results from the vignette. Let me know if I missed something.
library(curatedTCGAData)
library(TCGAutils)
coad_SE <- curatedTCGAData(
"COAD",
c("RNASeq2GeneNorm_illuminahiseq","Methylation_methyl450","GISTIC_AllByGene"),
version = "2.0.1",
dry.run = FALSE
)
## select only tumor samples
coad_SE <- TCGAprimaryTumors(coad_SE)
## only keep patients with observations in all assays
coad_ma <- MatchedAssayExperiment(coad_SE)
## keep NA MSI_status for Methylation data
coad_ma <- subsetByColData(
coad_ma, coad_ma$MSI_status == "MSI-H" | is.na(coad_ma$MSI_status)
)
rownames(coad_ma[["COAD_GISTIC_AllByGene-20160128"]]) <-
rowData(coad_ma[["COAD_GISTIC_AllByGene-20160128"]])[["Gene.Symbol"]]
data("gene_annot", package = "IntOMICS")
data("annot", package = "IntOMICS")
## create a named list to subset with
rowselect <- list(gene_annot$gene_symbol, gene_annot$gene_symbol, unlist(annot))
names(rowselect) <- names(coad_ma)
coad_ma[rowselect, , ]
Note. TCGAutils also has facilities for working with TCGA barcodes, e.g., TCGAbarcode()
Best regards, Marcel
Apropos the examples, you can use if (interactive()) in some cases to reduce time spent in testing examples. For MCMC, does the sample generation per se need to be tested? Can you run it once and store the samples so that the code using the samples is tested and illustrated for the user?
Thank you Marcel for your help, now I am able to implement the code you have suggested :) Ani Vince, thank you very much for the hint to if(interactive()), I have modify the examples according to your suggestion. Everything is pushed to the main repo at github.
Best wishes, Anna
čt 22. 9. 2022 v 21:38 odesílatel Vince Carey @.***> napsal:
Apropos the examples, you can use if (interactive()) in some cases to reduce time spent in testing examples. For MCMC, does the sample generation per se need to be tested? Can you run it once and store the samples so that the code using the samples is tested and illustrated for the user?
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Everything is pushed to the main repo at github.
Hi Anna,
Please make sure you are pushing to [email protected]:packages/IntOMICS as well.
Best,
Marcel
Thanks for all your hard work. I am still seeing issues as I try to build this package:
* creating vignettes ... ERROR
--- re-building ‘IntOMICS_vignette.Rmd’ using rmarkdown
Quitting from lines 109-134 (IntOMICS_vignette.Rmd)
Error: processing vignette 'IntOMICS_vignette.Rmd' failed with diagnostics:
HDF5. File accessibility. Unable to open file.
--- failed re-building ‘IntOMICS_vignette.Rmd’
As you make changes you should increase the z value in your version (x.y.z remains 0.99.0 at this time)
> sessionInfo()
R version 4.2.1 Patched (2022-10-05 r83030)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.5 LTS
Matrix products: default
BLAS: /home/stvjc/R-4-2-bc316-dist/lib/R/lib/libRblas.so
LAPACK: /home/stvjc/R-4-2-bc316-dist/lib/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[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] IntOMICS_0.99.0 rmarkdown_2.16
loaded via a namespace (and not attached):
[1] Rcpp_1.0.9 lubridate_1.8.0 lattice_0.20-45
[4] listenv_0.8.0 class_7.3-20 gtools_3.9.3
[7] assertthat_0.2.1 digest_0.6.29 ipred_0.9-13
[10] foreach_1.5.2 utf8_1.2.2 parallelly_1.32.1
[13] R6_2.5.1 hardhat_1.2.0 evaluate_0.16
[16] pillar_1.8.1 gplots_3.1.3 rlang_1.0.6
[19] rpart_4.1.16 Matrix_1.5-1 startup_0.18.0
[22] splines_4.2.1 gower_1.0.0 numbers_0.8-2
[25] igraph_1.3.5 compiler_4.2.1 xfun_0.33
[28] pkgconfig_2.0.3 bnstruct_1.0.12 globals_0.16.1
[31] htmltools_0.5.3 nnet_7.3-18 tidyselect_1.1.2
[34] tibble_3.1.8 prodlim_2019.11.13 bestNormalize_1.8.3
[37] matrixStats_0.62.0 codetools_0.2-18 fansi_1.0.3
[40] future_1.28.0 butcher_0.3.0 dplyr_1.0.10
[43] withr_2.5.0 MASS_7.3-58.1 bitops_1.0-7
[46] recipes_1.0.1 grid_4.2.1 lifecycle_1.0.2
[49] DBI_1.1.3 magrittr_2.0.3 KernSmooth_2.23-20
[52] future.apply_1.9.1 cli_3.4.1 doRNG_1.8.2
[55] doParallel_1.0.17 timeDate_4021.106 generics_0.1.3
[58] vctrs_0.4.2 lava_1.6.10 bnlearn_4.8.1
[61] RColorBrewer_1.1-3 iterators_1.0.14 tools_4.2.1
[64] glue_1.6.2 purrr_0.3.4 rngtools_1.5.2
[67] parallel_4.2.1 fastmap_1.1.0 survival_3.4-0
[70] caTools_1.18.2 knitr_1.40
@LiNk-NY: I am not sure how to push also to [email protected]:packages/IntOMICS. I tried to activate my account at https://git.bioconductor.org/BiocCredentials/account_activation/, but I got this error: [email protected] is not associated with a maintainer of a Bioconductor package. Am I using the correct link? @vjcitn: This could be because of the rhdf5 package, I added to the vignette. Let's see if it works.
You can not push to git.bioconductor.org yet -- @LiNk-NY was mistaken. You will have git access after the package passes pre-checks and @vjcitn marks it off. At that point it will be added to git and continue with an assigned reviewer. Currently updating your github repo will suffice for this stage
Dear Vince,
Are there any news about the IntOMICS package?
Thank you, Anna
Dne st 12. 10. 2022 17:05 uživatel lshep @.***> napsal:
You can not push to git.bioconductor.org yet -- @LiNk-NY https://github.com/LiNk-NY was mistaken. You will have git access after the package passes pre-checks and @vjcitn https://github.com/vjcitn marks it off. At that point it will be added to git and continue with an assigned reviewer. Currently updating your github repo will suffice for this stage
— Reply to this email directly, view it on GitHub https://github.com/Bioconductor/Contributions/issues/2744#issuecomment-1276332690, or unsubscribe https://github.com/notifications/unsubscribe-auth/AXW5J5E3N65ZL5YZODY5JATWC3HTDANCNFSM557T75OA . You are receiving this because you were mentioned.Message ID: @.***>
Dear @vjcitn,
Are there any news about the IntOMICS package?
Thank you,
Anna
Dne st 12. 10. 2022 17:05 uživatel lshep @.***> napsal:
You can not push to git.bioconductor.org yet -- @LiNk-NY https://github.com/LiNk-NY was mistaken. You will have git access after the package passes pre-checks and @vjcitn https://github.com/vjcitn marks it off. At that point it will be added to git and continue with an assigned reviewer. Currently updating your github repo will suffice for this stage
— Reply to this email directly, view it on GitHub https://github.com/Bioconductor/Contributions/issues/2744#issuecomment-1276332690, or unsubscribe https://github.com/notifications/unsubscribe-auth/AXW5J5E3N65ZL5YZODY5JATWC3HTDANCNFSM557T75OA . You are receiving this because you were mentioned.Message ID: @.***>
I have been unable to test the package but I think the problem is a broken cache on my end. So I have declared pre-check passed and the SPB and review can begin.
A reviewer has been assigned to your package. Learn what to expect during the review process.
IMPORTANT: Please read this documentation for setting up remotes to push to git.bioconductor.org. It is required to push a version bump to git.bioconductor.org to trigger a new build.
Bioconductor utilized your github ssh-keys for git.bioconductor.org access. To manage keys and future access you may want to active your Bioconductor Git Credentials Account
Dear Package contributor,
This is the automated single package builder at bioconductor.org.
Your package has been built on Linux, Mac, and Windows.
On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.
Please see the build report for more details. This link will be active for 21 days.
Remember: if you submitted your package after July 7th, 2020,
when making changes to your repository push to
[email protected]:packages/IntOMICS to trigger a new build.
A quick tutorial for setting up remotes and pushing to upstream can be found here.
Hello, I have removed the .gitignore file and added IntOMICS to my watched tags. Hope everything is OK. The new version 0.99.2 is pushed to the GitHub repo right now. I am not sure if [email protected]:packages/IntOMICS is active right now.
yes git.bioconductor.org is active and you will need to push the changes with a valid version bump there. Remember to activate your Bioconductor Git Credentials account as described in the previous comment
Received a valid push on git.bioconductor.org; starting a build for commit id: 3efa51f7eb0154990264808c4d5aa8a6b2d10612
Dear Package contributor,
This is the automated single package builder at bioconductor.org.
Your package has been built on Linux, Mac, and Windows.
On one or more platforms, the build results were: "ERROR". This may mean there is a problem with the package that you need to fix. Or it may mean that there is a problem with the build system itself.
Please see the build report for more details. This link will be active for 21 days.
Remember: if you submitted your package after July 7th, 2020,
when making changes to your repository push to
[email protected]:packages/IntOMICS to trigger a new build.
A quick tutorial for setting up remotes and pushing to upstream can be found here.
Received a valid push on git.bioconductor.org; starting a build for commit id: 172658d25ef84a6f770ccc2387ae90eb48315d2a