Entering edit mode
Dear all,
I have datasets from both EPIC and 450k, I am trying to use the RnBeads combine function to combine them into a single object.
This is example code from this tutorial, applied to the data provided in the tutorial: https://rnbeads.org/materials/data/tutorial/cross_platform/tutorial.html
When I run the following code, I get an error:
################ combine EPIC and 450k ##############
DIR_DATASETS<-"~/Downloads/"
# Let us now load each individual RnBSet object:
PLATFORMS<-c("450k", "EPIC")
rnb.sets<-list()
for(pl in PLATFORMS){
dfile<-sprintf("dataset-%s.zip", pl)
rnb.sets[[pl]]<-load.rnb.set(file.path(DIR_DATASETS, dfile))
}
> rnb.set.arrays<-combine(rnb.sets[["450k"]], rnb.sets[["EPIC"]], type="common")
Error in do.call(combine, list(y, ...)) :
argument "y" is missing, with no default
The same error happens with my own data (RnBeadRawSet). I don't get a combined RnBeadRawSet object out of either the tutorial or my own data. Is this a bug or am I using it wrong?
Thanks in advance!
R version 3.6.3 (2020-02-29)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.6 LTS
Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
locale:
[1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8
[5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8 LC_PAPER=en_GB.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grid stats4 parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] LOLA_1.14.0 GLAD_2.48.0 RnBeads.hg38_1.16.0
[4] GOstats_2.50.0 graph_1.62.0 Category_2.50.0
[7] Matrix_1.2-18 RnBeads_2.5.0 plyr_1.8.6
[10] methylumi_2.30.0 minfi_1.30.0 bumphunter_1.26.0
[13] locfit_1.5-9.4 iterators_1.0.12 foreach_1.5.0
[16] Biostrings_2.52.0 XVector_0.24.0 SummarizedExperiment_1.14.1
[19] DelayedArray_0.10.0 BiocParallel_1.18.1 FDb.InfiniumMethylation.hg19_2.2.0
[22] org.Hs.eg.db_3.8.2 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 GenomicFeatures_1.36.4
[25] AnnotationDbi_1.46.1 reshape2_1.4.4 scales_1.1.1
[28] Biobase_2.44.0 illuminaio_0.26.0 matrixStats_0.56.0
[31] limma_3.40.6 gridExtra_2.3 gplots_3.0.3
[34] ggplot2_3.3.1 fields_10.3 maps_3.3.0
[37] spam_2.5-1 dotCall64_1.0-0 ff_2.2-14.2
[40] bit_1.1-15.2 cluster_2.1.0 MASS_7.3-51.6
[43] GenomicRanges_1.36.1 GenomeInfoDb_1.20.0 IRanges_2.18.3
[46] S4Vectors_0.22.1 BiocGenerics_0.30.0
loaded via a namespace (and not attached):
[1] backports_1.1.7 GSEABase_1.46.0 splines_3.6.3 sva_3.32.1 digest_0.6.25
[6] GO.db_3.8.2 gdata_2.18.0 fansi_0.4.1 magrittr_1.5 memoise_1.1.0
[11] remotes_2.1.1 readr_1.3.1 annotate_1.62.0 askpass_1.1 siggenes_1.58.0
[16] prettyunits_1.1.1 colorspace_1.4-1 blob_1.2.1 dplyr_1.0.0 callr_3.4.3
[21] crayon_1.3.4 RCurl_1.98-1.2 genefilter_1.66.0 GEOquery_2.52.0 survival_3.1-12
[26] glue_1.4.1 gtable_0.3.0 zlibbioc_1.30.0 pkgbuild_1.0.8 Rgraphviz_2.28.0
[31] Rhdf5lib_1.6.3 HDF5Array_1.12.3 DBI_1.1.0 rngtools_1.5 Rcpp_1.0.4.6
[36] xtable_1.8-4 progress_1.2.2 mclust_5.4.6 preprocessCore_1.46.0 AnnotationForge_1.26.0
[41] httr_1.4.1 RColorBrewer_1.1-2 ellipsis_0.3.1 pkgconfig_2.0.3 reshape_0.8.8
[46] XML_3.99-0.3 tidyselect_1.1.0 rlang_0.4.6 munsell_0.5.0 tools_3.6.3
[51] cli_2.0.2 generics_0.0.2 RSQLite_2.2.0 stringr_1.4.0 yaml_2.2.1
[56] processx_3.4.2 bit64_0.9-7 beanplot_1.2 caTools_1.18.0 scrime_1.3.5
[61] purrr_0.3.4 RBGL_1.60.0 nlme_3.1-147 doRNG_1.8.2 nor1mix_1.3-0
[66] xml2_1.3.2 biomaRt_2.40.5 compiler_3.6.3 rstudioapi_0.11 curl_4.3
[71] tibble_3.0.1 stringi_1.4.6 ps_1.3.3 lattice_0.20-41 multtest_2.40.0
[76] vctrs_0.3.1 pillar_1.4.4 lifecycle_0.2.0 BiocManager_1.30.10 data.table_1.12.8
[81] bitops_1.0-6 rtracklayer_1.44.4 R6_2.4.1 KernSmooth_2.23-17 codetools_0.2-16
[86] gtools_3.8.2 assertthat_0.2.1 rhdf5_2.28.1 openssl_1.4.1 rprojroot_1.3-2
[91] withr_2.2.0 GenomicAlignments_1.20.1 Rsamtools_2.0.3 GenomeInfoDbData_1.2.1 mgcv_1.8-31
[96] hms_0.5.3 quadprog_1.5-8 tidyr_1.1.0 base64_2.0 DelayedMatrixStats_1.6.1
EDIT:
Hi all,
To rule out old packages I have updated R, bioconductor and Rnbeads to newest versions. Issue appears to be the same:
> DIR_DATASETS<-"~/Downloads/"
> PLATFORMS<-c("450k", "EPIC")
> rnb.sets<-list()
> for(pl in PLATFORMS){
+
+ dfile<-sprintf("dataset-%s.zip", pl)
+
+ rnb.sets[[pl]]<-load.rnb.set(file.path(DIR_DATASETS, dfile))
+
+ }
> rnb.set.arrays<-combine(rnb.sets[["450k"]], rnb.sets[["EPIC"]], type="common")
Error in h(simpleError(msg, call)) :
error in evaluating the argument 'y' in selecting a method for function 'combine': error in evaluating the argument 'y' in selecting a method for function 'combine': error in evaluating the argument 'args' in selecting a method for function 'do.call': argument "y" is missing, with no default
EDIT2: It seems to run when type isn't set at all. Setting it to anything causes the error code above. It is currently running, albeit with the default type (all) which seems to be inappropriate.
rnb.set.arrays<-combine(rnb.sets[["450k"]], rnb.sets[["EPIC"]])
Bug?
> sessionInfo()
R version 4.0.1 (2020-06-06)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.6 LTS
Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
locale:
[1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8
[5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8 LC_PAPER=en_GB.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grid stats4 parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] IlluminaHumanMethylationEPICmanifest_0.3.0 IlluminaHumanMethylation450kmanifest_0.4.0 doParallel_1.0.15
[4] LOLA_1.18.0 GLAD_2.52.0 RnBeads.hg38_1.20.0
[7] GOstats_2.54.0 graph_1.66.0 Category_2.54.0
[10] Matrix_1.2-18 RnBeads.hg19_1.20.0 RnBeads_2.6.0
[13] plyr_1.8.6 methylumi_2.34.0 minfi_1.34.0
[16] bumphunter_1.30.0 locfit_1.5-9.4 iterators_1.0.12
[19] foreach_1.5.0 Biostrings_2.56.0 XVector_0.28.0
[22] SummarizedExperiment_1.18.1 DelayedArray_0.14.0 FDb.InfiniumMethylation.hg19_2.2.0
[25] org.Hs.eg.db_3.11.4 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 GenomicFeatures_1.40.0
[28] AnnotationDbi_1.50.0 reshape2_1.4.4 scales_1.1.1
[31] Biobase_2.48.0 illuminaio_0.30.0 matrixStats_0.56.0
[34] limma_3.44.1 gridExtra_2.3 gplots_3.0.3
[37] ggplot2_3.3.1 fields_10.3 maps_3.3.0
[40] spam_2.5-1 dotCall64_1.0-0 ff_2.2-14.2
[43] bit_1.1-15.2 cluster_2.1.0 MASS_7.3-51.6
[46] GenomicRanges_1.40.0 GenomeInfoDb_1.24.0 IRanges_2.22.2
[49] S4Vectors_0.26.1 BiocGenerics_0.34.0
loaded via a namespace (and not attached):
[1] BiocFileCache_1.12.0 GSEABase_1.50.1 splines_4.0.1 BiocParallel_1.22.0 digest_0.6.25
[6] GO.db_3.11.4 gdata_2.18.0 magrittr_1.5 memoise_1.1.0 readr_1.3.1
[11] annotate_1.66.0 askpass_1.1 siggenes_1.62.0 prettyunits_1.1.1 colorspace_1.4-1
[16] blob_1.2.1 rappdirs_0.3.1 dplyr_1.0.0 crayon_1.3.4 RCurl_1.98-1.2
[21] genefilter_1.70.0 GEOquery_2.56.0 survival_3.1-12 glue_1.4.1 gtable_0.3.0
[26] zlibbioc_1.34.0 Rgraphviz_2.32.0 Rhdf5lib_1.10.0 HDF5Array_1.16.0 DBI_1.1.0
[31] rngtools_1.5 Rcpp_1.0.4.6 xtable_1.8-4 progress_1.2.2 mclust_5.4.6
[36] preprocessCore_1.50.0 AnnotationForge_1.30.1 httr_1.4.1 RColorBrewer_1.1-2 ellipsis_0.3.1
[41] farver_2.0.3 pkgconfig_2.0.3 reshape_0.8.8 XML_3.99-0.3 dbplyr_1.4.4
[46] labeling_0.3 tidyselect_1.1.0 rlang_0.4.6 munsell_0.5.0 tools_4.0.1
[51] generics_0.0.2 RSQLite_2.2.0 stringr_1.4.0 bit64_0.9-7 beanplot_1.2
[56] caTools_1.18.0 scrime_1.3.5 purrr_0.3.4 RBGL_1.64.0 nlme_3.1-147
[61] doRNG_1.8.2 nor1mix_1.3-0 xml2_1.3.2 biomaRt_2.44.0 compiler_4.0.1
[66] rstudioapi_0.11 curl_4.3 tibble_3.0.1 stringi_1.4.6 lattice_0.20-41
[71] multtest_2.44.0 vctrs_0.3.1 pillar_1.4.4 lifecycle_0.2.0 BiocManager_1.30.10
[76] data.table_1.12.8 bitops_1.0-6 rtracklayer_1.48.0 R6_2.4.1 KernSmooth_2.23-17
[81] codetools_0.2-16 gtools_3.8.2 assertthat_0.2.1 rhdf5_2.32.0 openssl_1.4.1
[86] withr_2.2.0 GenomicAlignments_1.24.0 Rsamtools_2.4.0 GenomeInfoDbData_1.2.3 hms_0.5.3
[91] quadprog_1.5-8 tidyr_1.1.0 base64_2.0 DelayedMatrixStats_1.10.0
Hi,
It does help when I combine two array data container, but now I want to combine 450K, RRBS and WGBS data, it seem that i came across the same problem as D did, how can i fix this ?
Hi,
For this task, you should first convert the
RnBeadSetobject into anRnBiseqSetobject using the constructorRnBiseqSet. Afterwards, you can use the functioncombine.