Hello,

Ran into this with setting up a design and thought it was interesting (and I can't figure out why). We have an RNA-Seq setup that we'd like to do some basic dose-response analysis (i.e., does expression change with increasing dosage of a drug?). We have a numeric column, Dose, that we use for this now. The thought was to change that to an ordered factor which better represents the data (or not). I created a new column as an ordered factor, DoseFactor, for this purpose, which contains the same information, just stored as a factor instead of a numeric.

Dose DoseFactor
   <dbl> <ord>     
 1  0.1  0.1       
 2  0    0         
 3  0.03 0.03      
 4  0.3  0.3       
 5  0    0         
 6  0.1  0.1       
 7  0.1  0.1       
 8  0.1  0.1       
 9  0.03 0.03      
10  0.3  0.3    

If I create the dataset using the numeric column, all is fine. However, with the factor column, I get this message:

DESeqDataSetFromMatrix(countData = countMatrix.1061,
                            colData = samplesubset.1061,
                            design = ~ DoseFactor)

Error in DESeqDataSet(se, design = design, ignoreRank) : 
  design contains one or more variables with all samples having the same value,
  remove these variables from the design

I would really appreciate anyone being able to shed light on this, or point me to the error in my thinking about this variable as a factor.

Thanks!

---

> sessionInfo()

R version 3.4.4 (2018-03-15)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.4

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/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] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] bindrcpp_0.2.2             reshape_0.8.7              geneplotter_1.56.0         lattice_0.20-35           
 [5] gridExtra_2.3              ggthemes_3.5.0             forcats_0.3.0              stringr_1.3.1             
 [9] purrr_0.2.4                readr_1.1.1                tidyr_0.8.1                tibble_1.4.2              
[13] tidyverse_1.2.1            RColorBrewer_1.1-2         DT_0.4                     plotly_4.7.1              
[17] ggplot2_2.2.1.9000         Glimma_1.6.0               readxl_1.1.0               gplots_3.0.1              
[21] fgsea_1.4.1                Rcpp_0.12.17               GSEABase_1.40.1            graph_1.56.0              
[25] annotate_1.56.2            XML_3.98-1.11              AnnotationDbi_1.40.0       DESeq2_1.18.1             
[29] SummarizedExperiment_1.8.1 DelayedArray_0.4.1         matrixStats_0.53.1         Biobase_2.38.0            
[33] GenomicRanges_1.30.3       GenomeInfoDb_1.14.0        IRanges_2.12.0             S4Vectors_0.16.0          
[37] BiocGenerics_0.24.0        pheatmap_1.0.10            magrittr_1.5               dplyr_0.7.5               
[41] plyr_1.8.4                 biomaRt_2.34.2            

loaded via a namespace (and not attached):
 [1] colorspace_1.3-2       rsconnect_0.8.8        rprojroot_1.3-2        htmlTable_1.11.2       XVector_0.18.0        
 [6] base64enc_0.1-3        rstudioapi_0.7         bit64_0.9-7            lubridate_1.7.4        xml2_1.2.0            
[11] splines_3.4.4          mnormt_1.5-5           knitr_1.20             Formula_1.2-3          jsonlite_1.5          
[16] broom_0.4.4            cluster_2.0.7-1        shiny_1.1.0            compiler_3.4.4         httr_1.3.1            
[21] backports_1.1.2        assertthat_0.2.0       Matrix_1.2-14          lazyeval_0.2.1         cli_1.0.0             
[26] limma_3.34.9           later_0.7.2            acepack_1.4.1          htmltools_0.3.6        prettyunits_1.0.2     
[31] tools_3.4.4            gtable_0.2.0           glue_1.2.0             GenomeInfoDbData_1.0.0 reshape2_1.4.3        
[36] fastmatch_1.1-0        cellranger_1.1.0       gdata_2.18.0           nlme_3.1-137           crosstalk_1.0.0       
[41] psych_1.8.4            rvest_0.3.2            mime_0.5               devtools_1.13.5        gtools_3.5.0          
[46] edgeR_3.20.9           zlibbioc_1.24.0        scales_0.5.0           promises_1.0.1         hms_0.4.2             
[51] yaml_2.1.19            memoise_1.1.0          rpart_4.1-13           latticeExtra_0.6-28    stringi_1.2.2         
[56] RSQLite_2.1.1          genefilter_1.60.0      checkmate_1.8.5        caTools_1.17.1         BiocParallel_1.12.0   
[61] rlang_0.2.0            pkgconfig_2.0.1        bitops_1.0-6           evaluate_0.10.1        bindr_0.1.1           
[66] labeling_0.3           htmlwidgets_1.2        bit_1.1-13             tidyselect_0.2.4       R6_2.2.2              
[71] Hmisc_4.1-1            DBI_1.0.0              pillar_1.2.2           haven_1.1.1            foreign_0.8-70        
[76] withr_2.1.2            survival_2.42-3        RCurl_1.95-4.10        nnet_7.3-12            crayon_1.3.4          
[81] modelr_0.1.2           utf8_1.1.3             KernSmooth_2.23-15     rmarkdown_1.9          progress_1.1.2        
[86] locfit_1.5-9.1         grid_3.4.4             data.table_1.10.4-3    blob_1.1.1             digest_0.6.15         
[91] xtable_1.8-2           httpuv_1.4.3           munsell_0.4.3          viridisLite_0.3.0 

The test you are seeing gives TRUE if all the values are equal to the first value in the factor. Something like all(DoseFactor == DoseFactor[1]). Can you think of a reason why this would return TRUE? Is that table you are showing the same as the one you use to create the dds?