DeSeq2 - Can't fetch any results: Error in .wrap_in_length_one_list_like_object(value, name, x)
1
0
Entering edit mode
@david-eccles-gringer-7488
Last seen 4.9 years ago
New Zealand

My script was working a month ago, but now it's not. I'm struggling with getting my DESeq2 analysis working. Here's what I'm trying to do:

factorNames <- c("Experiment", "Line");
dds <-
    DESeqDataSetFromMatrix(count.mat, meta.df,
                           as.formula(paste0("~ ", paste(factorNames,
                                                         collapse=" + "))));
dds <- DESeq(dds);
results(dds); # error happens after this command

Problem

What I would like to appear is a results table. I get the same error when I only specify a single variable in the formula, i.e.:

dds <- DESeqDataSetFromMatrix(count.mat, meta.df, ~ Line);
dds <- DESeq(dds);
results(dds); # error happens after this command

And this is the output:

Error in .wrap_in_length_one_list_like_object(value, name, x) : 
  failed to coerce 'list(value)' to a DESeqResults object of length 1

What else I've Tried (which still produce the error)

Reordering my library declarations at the start of my script:

library(DESeq2); library(tidyverse); library(magrittr);
## vs
library(tidyverse); library(magrittr); library(DESeq2);

Updating DESeq2 via BiocManager::install("DESeq2")

Possibly Useful Things

Here's the count matrix layout:

> str(count.mat)
 num [1:9934, 1:18] 1 0 7 0 0 0 0 45 379 392 ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:9934] "ENSMUST00000192271_rev" "ENSMUST00000127957_rev" "ENSMUST00000073783_fwd" "ENSMUST00000122876_rev" ...
  ..$ : chr [1:18] "CGJan19_006.BC08" "AJ_01-03_Jun19.BC01" "AJ_01-03_Jun19.BC02" "AJ_01-03_Jun19.BC03" ...

And my metadata data frame:

> meta.df
# A tibble: 18 x 5
   SampleID            Label                  Experiment Line   Replicate
   <chr>               <chr>                  <chr>      <fct>  <fct>    
 1 CGJan19_006.BC08    CG006.GL261ρ0_D106#A   CG006      p0D106 A        
 2 AJ_01-03_Jun19.BC01 AJJun19.GL261ρ0_D106#B AJJun19    p0D106 B        
 3 AJ_01-03_Jun19.BC02 AJJun19.GL261ρ0_D106#C AJJun19    p0D106 C        
 4 AJ_01-03_Jun19.BC03 AJJun19.GL261ρ0_D106#D AJJun19    p0D106 D        
 5 CGNov19_011.BC06    CGNov19.GL261ρ0_V1#A   CG011      p0V1   A        
 6 AJ_01-03_Jun19.BC09 AJJun19.GL261ρ0_V1#B   AJJun19    p0V1   B        
 7 AJ_01-03_Jun19.BC10 AJJun19.GL261ρ0_V1#C   AJJun19    p0V1   C        
 8 CGJan19_006.BC07    CG006.GL261ρ0_V3#A     CG006      p0V3   A        
 9 AJ_01-03_Jun19.BC04 AJJun19.GL261ρ0_V3#B   AJJun19    p0V3   B        
10 AJ_01-03_Jun19.BC05 AJJun19.GL261ρ0_V3#C   AJJun19    p0V3   C        
11 AJ_01-03_Jun19.BC06 AJJun19.GL261ρ0_V3#D   AJJun19    p0V3   D        
12 CGNov19_011.BC07    CGNov19.GL261.TMZR#A   CG011      TMZR   A        
13 CGNov19_011.BC08    CGNov19.GL261.TMZR#B   CG011      TMZR   B        
14 CGNov19_011.BC09    CGNov19.GL261.TMZR#C   CG011      TMZR   C        
15 CGJan19_006.BC06    CG006.GL261.WT#A       CG006      WT     A        
16 AJ_01-03_Jun19.BC07 AJJun19.GL261.WT#C     AJJun19    WT     C        
17 AJ_01-03_Jun19.BC08 AJJun19.GL261.WT#D     AJJun19    WT     D        
18 CGNov19_011.BC05    CGNov19.GL261.WT#D     CG011      WT     D

And finally, sessionInfo():

> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux bullseye/sid

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_NZ.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_NZ.UTF-8        LC_COLLATE=en_NZ.UTF-8    
 [5] LC_MONETARY=en_NZ.UTF-8    LC_MESSAGES=en_NZ.UTF-8   
 [7] LC_PAPER=en_NZ.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_NZ.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] DESeq2_1.24.0               SummarizedExperiment_1.16.0
 [3] DelayedArray_0.12.0         BiocParallel_1.20.0        
 [5] matrixStats_0.55.0          Biobase_2.46.0             
 [7] GenomicRanges_1.38.0        GenomeInfoDb_1.22.0        
 [9] IRanges_2.20.1              S4Vectors_0.24.1           
[11] BiocGenerics_0.32.0         magrittr_1.5               
[13] forcats_0.4.0               stringr_1.4.0              
[15] dplyr_0.8.3                 purrr_0.3.3                
[17] readr_1.3.1                 tidyr_1.0.0                
[19] tibble_2.1.3                ggplot2_3.2.1              
[21] tidyverse_1.3.0            

loaded via a namespace (and not attached):
 [1] nlme_3.1-142           bitops_1.0-6           fs_1.3.1              
 [4] bit64_0.9-7            lubridate_1.7.4        RColorBrewer_1.1-2    
 [7] httr_1.4.1             tools_3.6.1            backports_1.1.5       
[10] utf8_1.1.4             R6_2.4.1               rpart_4.1-15          
[13] Hmisc_4.3-0            DBI_1.0.0              lazyeval_0.2.2        
[16] colorspace_1.4-1       nnet_7.3-12            withr_2.1.2           
[19] tidyselect_0.2.5       gridExtra_2.3          bit_1.1-14            
[22] compiler_3.6.1         cli_1.1.0              rvest_0.3.5           
[25] htmlTable_1.13.3       xml2_1.2.2             scales_1.1.0          
[28] checkmate_1.9.4        genefilter_1.68.0      digest_0.6.23         
[31] foreign_0.8-72         XVector_0.26.0         base64enc_0.1-3       
[34] pkgconfig_2.0.3        htmltools_0.4.0        dbplyr_1.4.2          
[37] htmlwidgets_1.5.1      rlang_0.4.2            readxl_1.3.1          
[40] RSQLite_2.1.2          rstudioapi_0.10        generics_0.0.2        
[43] jsonlite_1.6           acepack_1.4.1          RCurl_1.95-4.12       
[46] GenomeInfoDbData_1.2.2 Formula_1.2-3          Matrix_1.2-18         
[49] fansi_0.4.0            Rcpp_1.0.3             munsell_0.5.0         
[52] lifecycle_0.1.0        stringi_1.4.3          zlibbioc_1.32.0       
[55] blob_1.2.0             grid_3.6.1             crayon_1.3.4          
[58] lattice_0.20-38        haven_2.2.0            splines_3.6.1         
[61] annotate_1.64.0        hms_0.5.2              locfit_1.5-9.1        
[64] zeallot_0.1.0          knitr_1.26             pillar_1.4.2          
[67] geneplotter_1.62.0     XML_3.98-1.20          reprex_0.3.0          
[70] glue_1.3.1             latticeExtra_0.6-28    data.table_1.12.6     
[73] BiocManager_1.30.10    modelr_0.1.5           vctrs_0.2.1           
[76] cellranger_1.1.0       gtable_0.3.0           assertthat_0.2.1      
[79] xfun_0.11              xtable_1.8-4           broom_0.5.3           
[82] survival_3.1-7         memoise_1.1.0          AnnotationDbi_1.48.0  
[85] cluster_2.1.0

Update [2019-Dec-20]

After comments from Mike Love, I've now uninstalled some packages from the base Debian system, and reinstalled packages into my local folders, and I'm getting a different error at a different step:

> dds <- DESeqDataSetFromMatrix(count.mat, meta.df, ~ Line);
converting counts to integer mode
Error in validObject(.Object) : 
  invalid class “DESeqDataSet” object: superclass "vector_OR_Vector" not defined in the environment of the object's class

So this seems to be an error due to a broken installation, and it's probably going to be difficult to get help for a problem relating to the specific combination of packages that my system decided to install. I'll have a go at wiping out the local R installation (i.e. rm -rf ~/R/x86_64-pc-linux-gnu-library), and reinstall DESeq2, and see where that gets me....

... and now it works. Thank you for bearing with me while I do the software equivalent of, "Have you tried turning it off and on again?"

> dds <-
+     DESeqDataSetFromMatrix(count.mat, meta.df,
+                            as.formula(paste0("~ ", paste(factorNames,
+                                                          collapse=" + "))));
converting counts to integer mode
Warning message:
In DESeqDataSet(se, design = design, ignoreRank) :
  some variables in design formula are characters, converting to factors
> dds <- DESeq(dds);
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
> results(dds);
log2 fold change (MLE): Line WT vs p0D106 
Wald test p-value: Line WT vs p0D106 
DataFrame with 9934 rows and 6 columns
                                baseMean      log2FoldChange             lfcSE
                               <numeric>           <numeric>         <numeric>
ENSMUST00000192271_rev  26563.2466352323   -1.09277749904499 0.377854584351656
ENSMUST00000127957_rev  9026.17510382961  -0.168498805001082 0.429131257538863
ENSMUST00000073783_fwd  7867.65681244628  -0.969776170520552 0.415097461404838
ENSMUST00000122876_rev  4950.21480608967  -0.906867087205864 0.316912053075736
ENSMUST00000154732_rev  3787.28318276015  -0.808128426231181 0.354406394204153
...                                  ...                 ...               ...
ENSMUST00000201831_fwd 0.755790685509435  -0.923018792648103  2.86138231601317
ENSMUST00000168645_fwd 0.670469974454824   -1.58950422743093  2.98741494666397
ENSMUST00000044373_fwd  1.49097034760506  -0.584856475816726  2.38605077355759
ENSMUST00000034452_fwd 0.588833538409114  -0.934693043540383  3.00417556365216
ENSMUST00000102758_rev  2.42279945004559 -0.0280350877040124  2.24570756265536
                                      stat              pvalue
                                 <numeric>           <numeric>
ENSMUST00000192271_rev   -2.89205833222863 0.00382726880343014
ENSMUST00000127957_rev  -0.392650971097864   0.694577287407033
ENSMUST00000073783_fwd   -2.33626138603325  0.0194776227007531
ENSMUST00000122876_rev   -2.86157335577621 0.00421543940158844
ENSMUST00000154732_rev    -2.2802309423505  0.0225939950836063
...                                    ...                 ...
ENSMUST00000201831_fwd  -0.322577932869232   0.747014908051351
ENSMUST00000168645_fwd  -0.532066772045149   0.594679750039667
ENSMUST00000044373_fwd  -0.245114849314253   0.806367505494896
ENSMUST00000034452_fwd  -0.311131298333338   0.755700808493421
ENSMUST00000102758_rev -0.0124838550531768   0.990039583510677
                                     padj
                                <numeric>
ENSMUST00000192271_rev 0.0826304581229773
ENSMUST00000127957_rev    0.9449149448463
ENSMUST00000073783_fwd  0.196809244865185
ENSMUST00000122876_rev 0.0884652702389295
ENSMUST00000154732_rev   0.21487097859105
...                                   ...
ENSMUST00000201831_fwd                 NA
ENSMUST00000168645_fwd                 NA
ENSMUST00000044373_fwd                 NA
ENSMUST00000034452_fwd                 NA
ENSMUST00000102758_rev                 NA
deseq2 software error • 2.1k views
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To my experience, that was a Rcpp issue. Please try to re-install your Rcpp package.

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@mikelove
Last seen 6 days ago
United States

Let’s go one step at a time.

You said this below produces an error?

dds <- DESeqDataSetFromMatrix(count.mat, meta.df, ~ Line)
dds <- DESeq(dds)
res <- results(dds)

Which step here gives an error?

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The very last step, producing the results table

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1
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Can you check if you have a valid installation of Bioc? There is a valid() function in BiocManager.

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No... 19 packages out-of-date; 18 packages too new. I'll see if running the recommended installations works for me:

> BiocManager::valid()

* sessionInfo()

R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux bullseye/sid

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_NZ.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_NZ.UTF-8        LC_COLLATE=en_NZ.UTF-8    
 [5] LC_MONETARY=en_NZ.UTF-8    LC_MESSAGES=en_NZ.UTF-8   
 [7] LC_PAPER=en_NZ.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_NZ.UTF-8 LC_IDENTIFICATION=C       

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

loaded via a namespace (and not attached):
[1] BiocManager_1.30.10 compiler_3.6.1      tools_3.6.1        

Bioconductor version '3.9'

  * 19 packages out-of-date
  * 18 packages too new

create a valid installation with

  BiocManager::install(c(
    "annotate", "AnnotationDbi", "Biobase", "BiocGenerics", "BiocParallel",
    "Biostrings", "cli", "data.table", "DBI", "DelayedArray", "DT",
    "genefilter", "GenomeInfoDb", "GenomeInfoDbData", "GenomicRanges", "GO.db",
    "httpuv", "IRanges", "later", "latticeExtra", "limma", "mime", "pillar",
    "plyr", "rlang", "rmarkdown", "RSQLite", "S4Vectors", "scales", "shiny",
    "SummarizedExperiment", "testthat", "tibble", "tinytex", "vctrs",
    "XVector", "zlibbioc"
  ), update = TRUE, ask = FALSE)

more details: BiocManager::valid()$too_new, BiocManager::valid()$out_of_date

Warning message:
19 packages out-of-date; 18 packages too new
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Entering edit mode

I have now uninstalled as many packages from the Debian system as it will let me get away with (i.e. without demanding that I also remove r-base), so that they could be updated in my user folder, and BiocManager::valid() now returns true:

> BiocManager::valid()
[1] TRUE

But BiocManager::install() still complains about non-updateable packages:

> BiocManager::install()
Bioconductor version 3.9 (BiocManager 1.30.10), R 3.6.1 (2019-07-05)
Installation path not writeable, unable to update packages: foreign, nlme,
  survival

Unfortunately things were broken in doing that uninstall. I also ran install.packages("pkgconfig", "png", "htmlwidgets", "xfun", "tidyverse", "xtable", "bit64", "blob", "memoise") to get the library(DESeq2) command happy. Presumably these were packages that were installed in the Debian base system, and BiocManager::valid() glossed over them.

* *sigh **

Debian....

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1
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I also can't guarantee that it will resolve this bug you saw, but hopefully it may.

Having a combination of packages across releases can lead to mysterious errors.

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