no method for coercing this S4 class to a vector #42
Comments
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Dear Joanne,
Thanks for trying out HoneyBADGER.
It looks like there may be some issues with using the S4 object class.
Can you please try running HoneyBADGER without using the `hb` object?
An example of the analysis without using objects is available under: https://jef.works/HoneyBADGER/Integrating.html
For example:
calcGexpCnvBoundaries(gexp.mats$gexp.norm, gexp.mats$genes, m=dev)
Jean Fan, PhD
Assistant Professor in Biomedical Engineering
Center for Computational Biology
Johns Hopkins University
web: jef.works<https://jef.works>
On Dec 5, 2020, at 3:17 PM, Joanne-PYL <[email protected]<mailto:[email protected]>> wrote:
External Email - Use Caution
Hi Dr. Fan,
Thank you so much for making this tool available. While running HoneyBADGER with my own .bam file and the reference provided, I ran into this error:
Error in jags.model(modelFile, data = data, inits = inits, n.chains = 4, :
no method for coercing this S4 class to a vector
while trying to generate HMM with
hb$calcGexpCnvBoundaries(init=TRUE, verbose=FALSE)
Here is my session info:
R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats4 parallel stats graphics grDevices utils
[7] datasets methods base
other attached packages:
[1] devtools_2.3.2
[2] usethis_1.6.3
[3] sos_2.0-2
[4] brew_1.0-6
[5] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[6] VariantAnnotation_1.36.0
[7] Rsamtools_2.6.0
[8] Biostrings_2.58.0
[9] XVector_0.30.0
[10] SummarizedExperiment_1.20.0
[11] MatrixGenerics_1.2.0
[12] matrixStats_0.57.0
[13] sparseMatrixUtils_0.1.0
[14] Matrix_1.2-18
[15] dplyr_1.0.2
[16] Seurat_3.2.2
[17] rjags_4-10
[18] coda_0.19-4
[19] biomaRt_2.46.0
[20] HoneyBADGER_0.1
[21] GenomicFeatures_1.42.1
[22] AnnotationDbi_1.52.0
[23] Biobase_2.50.0
[24] GenomicRanges_1.42.0
[25] GenomeInfoDb_1.26.1
[26] IRanges_2.24.0
[27] S4Vectors_0.28.0
[28] BiocGenerics_0.36.0
loaded via a namespace (and not attached):
[1] BiocFileCache_1.14.0 plyr_1.8.6
[3] igraph_1.2.6 lazyeval_0.2.2
[5] splines_4.0.3 BiocParallel_1.24.1
[7] listenv_0.8.0 ggplot2_3.3.2
[9] digest_0.6.27 htmltools_0.5.0
[11] HiddenMarkov_1.8-11 fansi_0.4.1
[13] magrittr_2.0.1 memoise_1.1.0
[15] BSgenome_1.58.0 tensor_1.5
[17] cluster_2.1.0 ROCR_1.0-11
[19] remotes_2.2.0 globals_0.14.0
[21] askpass_1.1 prettyunits_1.1.1
[23] colorspace_2.0-0 blob_1.2.1
[25] rappdirs_0.3.1 ggrepel_0.8.2
[27] callr_3.5.1 crayon_1.3.4
[29] RCurl_1.98-1.2 jsonlite_1.7.1
[31] spatstat_1.64-1 spatstat.data_1.5-2
[33] survival_3.2-7 zoo_1.8-8
[35] glue_1.4.2 polyclip_1.10-0
[37] gtable_0.3.0 zlibbioc_1.36.0
[39] leiden_0.3.5 DelayedArray_0.16.0
[41] pkgbuild_1.1.0 future.apply_1.6.0
[43] abind_1.4-5 scales_1.1.1
[45] DBI_1.1.0 miniUI_0.1.1.1
[47] Rcpp_1.0.5 viridisLite_0.3.0
[49] xtable_1.8-4 progress_1.2.2
[51] reticulate_1.18 bit_4.0.4
[53] rsvd_1.0.3 htmlwidgets_1.5.2
[55] httr_1.4.2 RColorBrewer_1.1-2
[57] ellipsis_0.3.1 ica_1.0-2
[59] pkgconfig_2.0.3 XML_3.99-0.5
[61] uwot_0.1.9 deldir_0.2-3
[63] dbplyr_2.0.0 tidyselect_1.1.0
[65] rlang_0.4.9 reshape2_1.4.4
[67] later_1.1.0.1 munsell_0.5.0
[69] tools_4.0.3 cli_2.2.0
[71] generics_0.1.0 RSQLite_2.2.1
[73] ggridges_0.5.2 stringr_1.4.0
[75] fastmap_1.0.1 goftest_1.2-2
[77] fs_1.5.0 processx_3.4.5
[79] bit64_4.0.5 fitdistrplus_1.1-3
[81] caTools_1.18.0 purrr_0.3.4
[83] RANN_2.6.1 pbapply_1.4-3
[85] future_1.20.1 nlme_3.1-150
[87] mime_0.9 xml2_1.3.2
[89] compiler_4.0.3 rstudioapi_0.13
[91] plotly_4.9.2.1 curl_4.3
[93] png_0.1-7 testthat_3.0.0
[95] spatstat.utils_1.17-0 tibble_3.0.4
[97] stringi_1.5.3 ps_1.4.0
[99] desc_1.2.0 lattice_0.20-41
[101] vctrs_0.3.5 pillar_1.4.7
[103] lifecycle_0.2.0 BiocManager_1.30.10
[105] lmtest_0.9-38 RcppAnnoy_0.0.17
[107] data.table_1.13.2 cowplot_1.1.0
[109] bitops_1.0-6 irlba_2.3.3
[111] httpuv_1.5.4 patchwork_1.1.0
[113] rtracklayer_1.50.0 R6_2.5.0
[115] promises_1.1.1 KernSmooth_2.23-18
[117] gridExtra_2.3 parallelly_1.21.0
[119] sessioninfo_1.1.1 codetools_0.2-18
[121] pkgload_1.1.0 MASS_7.3-53
[123] assertthat_0.2.1 rprojroot_2.0.2
[125] openssl_1.4.3 withr_2.3.0
[127] GenomicAlignments_1.26.0 sctransform_0.3.1
[129] GenomeInfoDbData_1.2.4 mgcv_1.8-33
[131] hms_0.5.3 grid_4.0.3
[133] rpart_4.1-15 tidyr_1.1.2
[135] Rtsne_0.15 shiny_1.5.0
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Hi Dr. Fan, Thank you for your reply. I am trying to run HoneyBADGER without 'hb' object, but I run into another problem. In your website, you use a lapply function when running 'calcAlleleCnvProb' function, which showed an error because of package updated. I am wondering that will the result be affected if I change the code to: If the function above is not working, can you give me some tips to revise the code? Thank you, |
|
Dear Joanne,
Without seeing the error, it is difficult for me to speculate on what may be happening here.
But to walk you through the code:
results <- do.call(rbind, lapply(potentialCnvs$region, function(region) {
calcAlleleCnvProb(...)
}))
'lapply' is looping through the regions in 'potentialCnvs$region’, which should be a list, and applying the 'calcAlleleCnvProb()' function and then combining them all into a final matrix that is saved as ‘results’
So if you would like to change the code to
results <- calcAlleleCnvProb(...)
You can do so by manually testing each of your regions. Ex:
region1 <- potentialCnvs$region[[1]]
results1 <- calcAlleleCnvProb(region1, …)
region2 <- potentialCnvs$region[[2]]
results2 <- calcAlleleCnvProb(region2, ...)
...
Jean Fan, PhD
Assistant Professor in Biomedical Engineering
Center for Computational Biology
Johns Hopkins University
web: jef.works<https://urldefense.proofpoint.com/v2/url?u=http-3A__jefworks.com_&d=DwMGaQ&c=WO-RGvefibhHBZq3fL85hQ&r=2gb0vmLv11Vi98WTAqlCXyDkhi11d9lKeGWDXEU-qNw&m=0o0gQ4rVt5tCCbfd0Dl2sjiItYey4i6Ke4JHKgvfS1I&s=U0ZAIxxhP7vb98fpV1FjD9qF1rQ9eIEqEE9M9igfOAc&e=>
On Dec 15, 2020, at 2:15 AM, Joanne-PYL <[email protected]<mailto:[email protected]>> wrote:
External Email - Use Caution
Hi Dr. Fan,
Thank you for your reply. I am trying to run HoneyBADGER without 'hb' object, but I run into another problem.
In your website, you use a lapply function when running 'calcAlleleCnvProb' function, which showed an error because of package updated.
results <- do.call(rbind, lapply(potentialCnvs$region, function(region) {
calcAlleleCnvProb(...)
}))
I am wondering that will the result be affected if I change the code to:
results <- calcAlleleCnvProb(...)
If the function above is not working, can you give me some tips to revise the code?
Thank you,
Joanne
—
You are receiving this because you commented.
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Hi Dr. Fan,
Thank you so much for making this tool available. While running HoneyBADGER with my own .bam file and the reference provided, I ran into this error:
Error in jags.model(modelFile, data = data, inits = inits, n.chains = 4, :
no method for coercing this S4 class to a vector
while trying to generate HMM with
hb$calcGexpCnvBoundaries(init=TRUE, verbose=FALSE)
Here is my session info:
R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats4 parallel stats graphics grDevices utils
[7] datasets methods base
other attached packages:
[1] devtools_2.3.2
[2] usethis_1.6.3
[3] sos_2.0-2
[4] brew_1.0-6
[5] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[6] VariantAnnotation_1.36.0
[7] Rsamtools_2.6.0
[8] Biostrings_2.58.0
[9] XVector_0.30.0
[10] SummarizedExperiment_1.20.0
[11] MatrixGenerics_1.2.0
[12] matrixStats_0.57.0
[13] sparseMatrixUtils_0.1.0
[14] Matrix_1.2-18
[15] dplyr_1.0.2
[16] Seurat_3.2.2
[17] rjags_4-10
[18] coda_0.19-4
[19] biomaRt_2.46.0
[20] HoneyBADGER_0.1
[21] GenomicFeatures_1.42.1
[22] AnnotationDbi_1.52.0
[23] Biobase_2.50.0
[24] GenomicRanges_1.42.0
[25] GenomeInfoDb_1.26.1
[26] IRanges_2.24.0
[27] S4Vectors_0.28.0
[28] BiocGenerics_0.36.0
loaded via a namespace (and not attached):
[1] BiocFileCache_1.14.0 plyr_1.8.6
[3] igraph_1.2.6 lazyeval_0.2.2
[5] splines_4.0.3 BiocParallel_1.24.1
[7] listenv_0.8.0 ggplot2_3.3.2
[9] digest_0.6.27 htmltools_0.5.0
[11] HiddenMarkov_1.8-11 fansi_0.4.1
[13] magrittr_2.0.1 memoise_1.1.0
[15] BSgenome_1.58.0 tensor_1.5
[17] cluster_2.1.0 ROCR_1.0-11
[19] remotes_2.2.0 globals_0.14.0
[21] askpass_1.1 prettyunits_1.1.1
[23] colorspace_2.0-0 blob_1.2.1
[25] rappdirs_0.3.1 ggrepel_0.8.2
[27] callr_3.5.1 crayon_1.3.4
[29] RCurl_1.98-1.2 jsonlite_1.7.1
[31] spatstat_1.64-1 spatstat.data_1.5-2
[33] survival_3.2-7 zoo_1.8-8
[35] glue_1.4.2 polyclip_1.10-0
[37] gtable_0.3.0 zlibbioc_1.36.0
[39] leiden_0.3.5 DelayedArray_0.16.0
[41] pkgbuild_1.1.0 future.apply_1.6.0
[43] abind_1.4-5 scales_1.1.1
[45] DBI_1.1.0 miniUI_0.1.1.1
[47] Rcpp_1.0.5 viridisLite_0.3.0
[49] xtable_1.8-4 progress_1.2.2
[51] reticulate_1.18 bit_4.0.4
[53] rsvd_1.0.3 htmlwidgets_1.5.2
[55] httr_1.4.2 RColorBrewer_1.1-2
[57] ellipsis_0.3.1 ica_1.0-2
[59] pkgconfig_2.0.3 XML_3.99-0.5
[61] uwot_0.1.9 deldir_0.2-3
[63] dbplyr_2.0.0 tidyselect_1.1.0
[65] rlang_0.4.9 reshape2_1.4.4
[67] later_1.1.0.1 munsell_0.5.0
[69] tools_4.0.3 cli_2.2.0
[71] generics_0.1.0 RSQLite_2.2.1
[73] ggridges_0.5.2 stringr_1.4.0
[75] fastmap_1.0.1 goftest_1.2-2
[77] fs_1.5.0 processx_3.4.5
[79] bit64_4.0.5 fitdistrplus_1.1-3
[81] caTools_1.18.0 purrr_0.3.4
[83] RANN_2.6.1 pbapply_1.4-3
[85] future_1.20.1 nlme_3.1-150
[87] mime_0.9 xml2_1.3.2
[89] compiler_4.0.3 rstudioapi_0.13
[91] plotly_4.9.2.1 curl_4.3
[93] png_0.1-7 testthat_3.0.0
[95] spatstat.utils_1.17-0 tibble_3.0.4
[97] stringi_1.5.3 ps_1.4.0
[99] desc_1.2.0 lattice_0.20-41
[101] vctrs_0.3.5 pillar_1.4.7
[103] lifecycle_0.2.0 BiocManager_1.30.10
[105] lmtest_0.9-38 RcppAnnoy_0.0.17
[107] data.table_1.13.2 cowplot_1.1.0
[109] bitops_1.0-6 irlba_2.3.3
[111] httpuv_1.5.4 patchwork_1.1.0
[113] rtracklayer_1.50.0 R6_2.5.0
[115] promises_1.1.1 KernSmooth_2.23-18
[117] gridExtra_2.3 parallelly_1.21.0
[119] sessioninfo_1.1.1 codetools_0.2-18
[121] pkgload_1.1.0 MASS_7.3-53
[123] assertthat_0.2.1 rprojroot_2.0.2
[125] openssl_1.4.3 withr_2.3.0
[127] GenomicAlignments_1.26.0 sctransform_0.3.1
[129] GenomeInfoDbData_1.2.4 mgcv_1.8-33
[131] hms_0.5.3 grid_4.0.3
[133] rpart_4.1-15 tidyr_1.1.2
[135] Rtsne_0.15 shiny_1.5.0
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