problem download some data from one project

[bioinfo-dirty-jobs]

I use this version: GenomicDataCommons::status() $commit [1] "e588f035feefee17f562b3a1bc2816c49a2b2b19" $data_release [1] "Data Release 16.0 - March 26, 2019" $status [1] "OK" $tag [1] "1.20.0" $version [1] 1

But I'm not able to download this data...

dati2=files() %>% filter( ~ cases.project.project_id == "TCGA-LAML" &
+                               data_type == "Gene Expression Quantification" &
+                               analysis.workflow_type=="HTSeq - FPKM-UQ" & cases.samples.sample_type =='Primary Tumor')  %>% results_all()
> dati2
list()
attr(,"class")
ttr(,"class")
[1] "GDCfilesResults" "GDCResults"      "list"           
> sessionInfo()
R version 3.5.2 (2018-12-20)
Platform: x86_64-redhat-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8       
 [4] LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggplot2_3.1.1            TCGAutils_1.2.2          BiocManager_1.30.4      
[4] h2o_3.22.1.1             GenomicDataCommons_1.6.0 magrittr_1.5            

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.1                  lattice_0.20-38             gtools_3.8.1               
 [4] prettyunits_1.0.2           Rsamtools_1.34.1            Biostrings_2.50.2          
 [7] assertthat_0.2.1            digest_0.6.18               plyr_1.8.4                 
[10] R6_2.4.0                    GenomeInfoDb_1.18.2         stats4_3.5.2               
[13] RSQLite_2.1.1               httr_1.4.0                  pillar_1.3.1               
[16] zlibbioc_1.28.0             rlang_0.3.4                 GenomicFeatures_1.34.8     
[19] progress_1.2.0              lazyeval_0.2.2              curl_3.3                   
[22] rstudioapi_0.10             blob_1.1.1                  S4Vectors_0.20.1           
[25] Matrix_1.2-15               labeling_0.3                BiocParallel_1.16.6        
[28] readr_1.3.1                 stringr_1.4.0               munsell_0.5.0              
[31] RCurl_1.95-4.12             bit_1.1-14                  biomaRt_2.38.0             
[34] DelayedArray_0.8.0          compiler_3.5.2              rtracklayer_1.42.2         
[37] pkgconfig_2.0.2             BiocGenerics_0.28.0         tidyselect_0.2.5           
[40] SummarizedExperiment_1.12.0 tibble_2.1.1                GenomeInfoDbData_1.2.0     
[43] IRanges_2.16.0              matrixStats_0.54.0          XML_3.98-1.19              
[46] withr_2.1.2                 crayon_1.3.4                dplyr_0.8.0.1              
[49] GenomicAlignments_1.18.1    bitops_1.0-6                rappdirs_0.3.1             
[52] grid_3.5.2                  jsonlite_1.6                gtable_0.3.0               
[55] DBI_1.0.0                   scales_1.0.0                stringi_1.4.3              
[58] XVector_0.22.0              MultiAssayExperiment_1.8.3  xml2_1.2.0                 
[61] tools_3.5.2                 bit64_0.9-7                 Biobase_2.42.0             
[64] glue_1.3.1                  purrr_0.3.2                 hms_0.4.2                  
[67] parallel_3.5.2              colorspace_1.4-1            AnnotationDbi_1.44.0       
[70] GenomicRanges_1.34.0        rvest_0.3.3                 memoise_1.1.0 

[seandavi]

I think the cases.samples.sample_type =='Primary Tumor') is killing this one. Take a look at the available_values() for that field. I think there is probably a possible value that includes blood cancer or some such thing. Alternatively, just remove the samples_type filter altogether and filter in R based on results.

I'll close for now, but definitely let me know if you need further guidance/help.

[bioinfo-dirty-jobs]

@seandavi Thanks so much!