Problem constructing DESeq objects with large integers.
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0
Entering edit mode
Zach Brehm • 0
@zach-brehm-16642
Last seen 4.8 years ago

Hello,

I am attempting to construct a dds object out some GTEx data obtained through Recount. When creating the dds object, I am met with an error that I believe is due to integers in the data that are too large for R. I have been unable to find a workaround for this thus far. The following output displays the command that generated the error, the error itself, and my session info.

Thanks, Zach

> dds_merge <- DESeqDataSet(rse_merge, design = ~1) %>% estimateSizeFactors()
converting counts to integer mode
Error in validObject(.Object) : 
  invalid class “DESeqDataSet” object: NA values are not allowed in the count matrix
In addition: Warning message:
In mde(x) : NAs introduced by coercion to integer range
> sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 16299)

Matrix products: default

Random number generation:
 RNG:     Mersenne-Twister 
 Normal:  Inversion 
 Sample:  Rounding 

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] forcats_0.4.0               stringr_1.4.0               dplyr_0.8.0.1              
 [4] purrr_0.3.2                 readr_1.3.1                 tidyr_0.8.3                
 [7] tibble_2.1.1                ggplot2_3.1.1               tidyverse_1.2.1            
[10] DESeq2_1.24.0               SummarizedExperiment_1.14.0 DelayedArray_0.10.0        
[13] BiocParallel_1.17.18        matrixStats_0.54.0          Biobase_2.44.0             
[16] GenomicRanges_1.36.0        GenomeInfoDb_1.20.0         IRanges_2.18.0             
[19] S4Vectors_0.22.0            BiocGenerics_0.30.0        

loaded via a namespace (and not attached):
 [1] nlme_3.1-139           bitops_1.0-6           lubridate_1.7.4        bit64_0.9-7           
 [5] RColorBrewer_1.1-2     httr_1.4.0             tools_3.6.0            backports_1.1.4       
 [9] R6_2.4.0               rpart_4.1-15           Hmisc_4.2-0            DBI_1.0.0             
[13] lazyeval_0.2.2         colorspace_1.4-1       nnet_7.3-12            withr_2.1.2           
[17] tidyselect_0.2.5       gridExtra_2.3          bit_1.1-14             compiler_3.6.0        
[21] cli_1.1.0              rvest_0.3.3            htmlTable_1.13.1       xml2_1.2.0            
[25] scales_1.0.0           checkmate_1.9.3        genefilter_1.66.0      digest_0.6.18         
[29] foreign_0.8-71         XVector_0.24.0         base64enc_0.1-3        pkgconfig_2.0.2       
[33] htmltools_0.3.6        htmlwidgets_1.3        rlang_0.3.4            readxl_1.3.1          
[37] rstudioapi_0.10        RSQLite_2.1.1          generics_0.0.2         jsonlite_1.6          
[41] acepack_1.4.1          RCurl_1.95-4.12        magrittr_1.5           GenomeInfoDbData_1.2.1
[45] Formula_1.2-3          Matrix_1.2-17          Rcpp_1.0.1             munsell_0.5.0         
[49] stringi_1.4.3          zlibbioc_1.30.0        plyr_1.8.4             grid_3.6.0            
[53] blob_1.1.1             crayon_1.3.4           lattice_0.20-38        haven_2.1.0           
[57] splines_3.6.0          annotate_1.62.0        hms_0.4.2              locfit_1.5-9.1        
[61] knitr_1.22             pillar_1.4.0           geneplotter_1.62.0     XML_3.98-1.19         
[65] glue_1.3.1             latticeExtra_0.6-28    data.table_1.12.2      modelr_0.1.4          
[69] cellranger_1.1.0       gtable_0.3.0           assertthat_0.2.1       xfun_0.7              
[73] xtable_1.8-4           broom_0.5.2            survival_2.44-1.1      AnnotationDbi_1.46.0  
[77] memoise_1.1.0          cluster_2.0.8         
deseq2 recount • 1.8k views
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Entering edit mode
@mikelove
Last seen 17 hours ago
United States

Are you sure that you don't have an NA in the counts?

You can use anyis.na(...)) on the counts assay for example to test this yourself.

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Entering edit mode

Yes, but to be safe I just double checked them with the following:

> max(assay(rse_merge)) - .Machine$integer.max
[1] 13994598706
> anyis.na(assay(rse_merge)))
[1] FALSE
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Entering edit mode

Maybe you can follow up with the creators of the object as to why there is a seemingly erroneous value in the assay.

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