404 not found error in dataman_2019.Rmd #82
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dbListTables(tcgaCon)
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1: [email protected]
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[1] "Copy_Number_Segment_Masked" "Copy_Number_Segment_Masked_r14"
[3] "DNA_Methylation" "DNA_Methylation_chr1"
[5] "DNA_Methylation_chr10" "DNA_Methylation_chr11"
[7] "DNA_Methylation_chr12" "DNA_Methylation_chr13" ...
The command you mention does work if the tcgaCon connection is valid.
CGC_BILLING needs
to be an environment variable that has been set before the R session
started, to refer
to an active google cloud platform project id.
…On Mon, Sep 9, 2019 at 9:45 PM gillsignals ***@***.***> wrote:
Lines 875-877 of dataman_2019.Rmd generate a 404 not found error after
authenticating with Google BigQuery and returning to R as directed by the
browser:
tcgaCon %>% tbl("Somatic_Mutation") %>% dplyr::filter(project_short_name=="TCGA-GBM") %>%
dplyr::select(Variant_Classification, Hugo_Symbol) %>% group_by(Variant_Classification) %>%
summarise(n=n())
Error: HTTP error [404] Not Found
Is this the appropriate workflow? If so, what do learners need to know or
do in order to not encounter this 404 error?
> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17763)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252
attached base packages:
[1] grid stats4 parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] magrittr_1.5 dplyr_0.8.3
[3] bigrquery_1.2.0 RaggedExperiment_1.8.0
[5] curatedTCGAData_1.6.0 MultiAssayExperiment_1.10.4
[7] VariantTools_1.26.0 VariantAnnotation_1.30.1
[9] ph525x_0.0.48 png_0.1-7
[11] ldblock_1.14.2 erma_1.0.0
[13] Homo.sapiens_1.3.1 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[15] OrganismDbi_1.26.0 GenomicFeatures_1.36.4
[17] GenomicAlignments_1.20.1 GenomicFiles_1.20.0
[19] rtracklayer_1.44.2 Rsamtools_2.0.0
[21] RNAseqData.HNRNPC.bam.chr14_0.22.0 IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0
[23] IlluminaHumanMethylation450kmanifest_0.4.0 minfi_1.30.0
[25] bumphunter_1.26.0 locfit_1.5-9.1
[27] iterators_1.0.12 foreach_1.4.7
[29] Biostrings_2.52.0 XVector_0.24.0
[31] data.table_1.12.2 GO.db_3.8.2
[33] org.Hs.eg.db_3.8.2 airway_1.4.0
[35] SummarizedExperiment_1.14.1 DelayedArray_0.10.0
[37] BiocParallel_1.18.1 matrixStats_0.54.0
[39] GenomicRanges_1.36.0 GenomeInfoDb_1.20.0
[41] ArrayExpress_1.44.0 GEOquery_2.52.0
[43] annotate_1.62.0 XML_3.98-1.20
[45] AnnotationDbi_1.46.1 IRanges_2.18.1
[47] S4Vectors_0.22.0 Biobase_2.44.0
[49] BiocGenerics_0.30.0 GSE5859Subset_1.0
loaded via a namespace (and not attached):
[1] tidyselect_0.2.5 RSQLite_2.1.2 munsell_0.5.0 codetools_0.2-16
[5] preprocessCore_1.46.0 withr_2.1.2 colorspace_1.4-1 knitr_1.24
[9] rstudioapi_0.10 labeling_0.3 GenomeInfoDbData_1.2.1 bit64_0.9-7
[13] rhdf5_2.28.0 vctrs_0.2.0 xfun_0.9 BiocFileCache_1.8.0
[17] affxparser_1.56.0 R6_2.4.0 illuminaio_0.26.0 AnnotationFilter_1.8.0
[21] bitops_1.0-6 reshape_0.8.8 assertthat_0.2.1 promises_1.0.1
[25] scales_1.0.0 gtable_0.3.0 ensembldb_2.8.0 rlang_0.4.0
[29] zeallot_0.1.0 genefilter_1.66.0 splines_3.6.1 lazyeval_0.2.2
[33] gargle_0.3.1 BiocManager_1.30.4 yaml_2.2.0 reshape2_1.4.3
[37] snpStats_1.34.0 backports_1.1.4 httpuv_1.5.1 RBGL_1.60.0
[41] tools_3.6.1 nor1mix_1.3-0 ggplot2_3.2.1 affyio_1.54.0
[45] ff_2.2-14 RColorBrewer_1.1-2 siggenes_1.58.0 Rcpp_1.0.1
[49] plyr_1.8.4 progress_1.2.2 zlibbioc_1.30.0 purrr_0.3.2
[53] RCurl_1.95-4.12 prettyunits_1.0.2 openssl_1.4.1 fs_1.3.1
[57] ProtGenerics_1.16.0 hms_0.5.1 mime_0.7 xtable_1.8-4
[61] mclust_5.4.5 gridExtra_2.3 compiler_3.6.1 biomaRt_2.40.4
[65] tibble_2.1.3 crayon_1.3.4 htmltools_0.3.6 later_0.8.0
[69] snow_0.4-3 tidyr_0.8.3 oligo_1.48.0 DBI_1.0.0
[73] ExperimentHub_1.10.0 dbplyr_1.4.2 MASS_7.3-51.4 rappdirs_0.3.1
[77] EnsDb.Hsapiens.v75_2.99.0 Matrix_1.2-17 readr_1.3.1 quadprog_1.5-7
[81] pkgconfig_2.0.2 registry_0.5-1 xml2_1.2.2 rngtools_1.4
[85] pkgmaker_0.27 multtest_2.40.0 beanplot_1.2 bibtex_0.4.2
[89] doRNG_1.7.1 scrime_1.3.5 stringr_1.4.0 digest_0.6.20
[93] graph_1.62.0 base64_2.0 DelayedMatrixStats_1.6.0 curl_4.0
[97] shiny_1.3.2 jsonlite_1.6 nlme_3.1-141 Rhdf5lib_1.6.0
[101] askpass_1.1 limma_3.40.6 BSgenome_1.52.0 pillar_1.4.2
[105] lattice_0.20-38 httr_1.4.1 survival_2.44-1.1 interactiveDisplayBase_1.22.0
[109] glue_1.3.1 UpSetR_1.4.0 bit_1.1-14 stringi_1.4.3
[113] HDF5Array_1.12.2 blob_1.2.0 oligoClasses_1.46.0 AnnotationHub_2.16.1
[117] memoise_1.1.0
Thanks!
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The first part did work after authentication in the browser, but the subsequent command yields the 404 error. Is a valid Google Cloud platform project ID strictly required to perform this operation? I would strongly suppose that 95% of learners in the course will not have this ID and be unable to run this code when they copy it to their personal machine. We try to have all the code in our courses be fully replicable by learners if they copy-paste or download the Rmd files. Is there any way to do this operation without requiring a project/billing ID or environment variable? |
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On Tue, Sep 10, 2019 at 6:31 AM gillsignals ***@***.***> wrote:
The first part did work after authentication in the browser, but the
subsequent command yields the 404 error.
Is a valid Google Cloud platform project ID strictly required to perform
this operation? I would strongly suppose that 95% of learners in the course
will not have this ID and be unable to run this code when they copy it to
their personal machine.
We try to have all the code in our courses be fully replicable by learners
if they copy-paste or download the Rmd files. Is there any way to do this
operation without requiring a project/billing ID or environment variable?
No. It should be removed or made optional for those who are willing to get
a project id. Can you issue a pull request that removes or makes these
computational conditional
on availability of a non-null value for CGC_BILLING?
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The reason I haven't fixed this yet is because the problem sets still require the results of this operation. When we meet, we can talk about fully replacing those exercises and/or moving this to an optional section without exercises (and possibly in course 6 instead of course 5, since it's more advanced). Thanks! |
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Lines 875-877 of dataman_2019.Rmd generate a 404 not found error after authenticating with Google BigQuery and returning to R as directed by the browser:
Is this the appropriate workflow? If so, what do learners need to know or do in order to not encounter this 404 error?
Thanks!
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