Hello,

I am attempting to re-run a script to find differentially expressed genes using DESeq2 that ran correctly two days ago. Since then, I updated R from version 3.3.2 to version 3.3.3. When attempting to call the DESeq function today, I get the following error:

Error in .Primitive("c")(<S4 object of class "GRangesList">, <S4 object of class "GRangesList">,  :
  could not find symbol "recursive" in environment of the generic function

I have updated the GenomicRanges package, but this has not fixed the problem.

Does anybody know what the problem might be? Should I revert to version 3.3.2 of R for the time being?

Thanks!

Erin

I've pasted my code below.

###################################################################

samples = read.csv("samples.csv",header=TRUE)

#remove libraries that have fewer than 750,000 reads
samples<-samples[samples$libsize >= 750000, ]

#start edgeR, which you will use to make the count matrix
library("edgeR")

#proceed to read in count data from .count files, filter counts
counts = readDGE(samples$countf)$counts
noint = rownames(counts) %in%
 
  c("__no_feature","__ambiguous","__too_low_aQual",
    
    "__not_aligned","__alignment_not_unique")

cpms = cpm(counts)

keep = rowSums(cpms >3) >=2 & !noint

counts = counts[keep,]

colnames(counts) = samples$shortname

#attach the column data to from the sample sheet to the variable coldata
coldata = with(samples,data.frame(shortname = I(shortname), condition = condition))

#attach the count data to the variable countdata
countdata = counts

#start DESeq2
library("DESeq2")

#construct your DESeq2 data set, making sure to specify the design matrix here
dds <- DESeqDataSetFromMatrix(countData = countdata,
                              colData = coldata,
                              design = ~ condition)

#run DESeq2 on the dataset
dds <- DESeq(dds, parallel=TRUE)

###########################################

My sample sheet is as follows:

#######################################################

sessionInfo()

R version 3.3.3 (2017-03-06)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.2 LTS

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

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

other attached packages:
 [1] ggplot2_2.2.1              gplots_3.0.1               RColorBrewer_1.1-2        
 [4] DESeq2_1.14.1              SummarizedExperiment_1.4.0 Biobase_2.34.0            
 [7] GenomicRanges_1.26.3       GenomeInfoDb_1.10.3        IRanges_2.8.1             
[10] S4Vectors_0.12.1           BiocGenerics_0.20.0        edgeR_3.16.5              
[13] limma_3.30.12             

loaded via a namespace (and not attached):
 [1] genefilter_1.56.0    gtools_3.5.0         locfit_1.5-9.1       splines_3.3.3       
 [5] lattice_0.20-34      colorspace_1.3-2     htmltools_0.3.5      base64enc_0.1-3     
 [9] survival_2.40-1      XML_3.98-1.5         foreign_0.8-67       DBI_0.6             
[13] BiocParallel_1.8.1   plyr_1.8.4           stringr_1.2.0        zlibbioc_1.20.0     
[17] munsell_0.4.3        gtable_0.2.0         caTools_1.17.1       htmlwidgets_0.8     
[21] memoise_1.0.0        labeling_0.3         latticeExtra_0.6-28  knitr_1.15.1        
[25] geneplotter_1.52.0   AnnotationDbi_1.36.2 htmlTable_1.9        Rcpp_0.12.9         
[29] KernSmooth_2.23-15   acepack_1.4.1        xtable_1.8-2         scales_0.4.1        
[33] backports_1.0.5      checkmate_1.8.2      gdata_2.17.0         Hmisc_4.0-2         
[37] annotate_1.52.1      XVector_0.14.0       gridExtra_2.2.1      digest_0.6.12       
[41] stringi_1.1.2        grid_3.3.3           tools_3.3.3          bitops_1.0-6        
[45] magrittr_1.5         lazyeval_0.2.0       RCurl_1.95-4.8       tibble_1.2          
[49] RSQLite_1.1-2        Formula_1.2-1        cluster_2.0.5        Matrix_1.2-8        
[53] data.table_1.10.4    assertthat_0.1       rpart_4.1-10         nnet_7.3-12

Please see these questions A: Combining RangedData objects is broken (IRanges 2.8.1 with R version 3.3.3 RC) A: rGADEM error retrieving sequences. I think the problem is from installing a new R over an old package library; while in principle this is supposed to work, it clearly is not.

Thank you for your response, Martin.

I have also managed to fix the error by omitting

parallel=TRUE

from the last line of my code. Therefore, the issue may actually lie in the BiocParallel library.