DESeqDataSetFromMatrix Error in if/while (condition) {: missing Value where TRUE/FALSE needed

Question

[johannes.wedel]

Hi,

I am new to R and try to analyze a RNA-seq experiment using DESeq2. I've got a pretty simple RNAseq experiment (3 conditions, 2 biological replicates) but I'm having trouble getting the count data into DESeq2.

I used several ways to import my data, however always get the same error:

Error in if/while (condition) {: missing Value where TRUE/FALSE needed

Could anybody explain what is wrong?

Thank you in advance!

Johannes

countData <- as.matrix(read.table ("Seq_unnorm_null.txt", header = TRUE, sep = "\t", row.names = 1)) 
colData = read.table ("Seq_r_cond.txt", header = TRUE, sep = "\t", row.names = 1)
colData [["condition"]] = factor(colData[["condition"]], levels = c("inflamm", "Treg", "none"))
head(countData)
              BM12_1 BM12_2      Treg_1 Treg_2 Con_1 Con_2
1700086P04Rik      0      0 1.43484e+11      0     0     0
3300005D01Rik      0      0 1.43484e+11      0     0     0
4933430I17Rik      0      0 1.43484e+11      0     0     0
5730507C01Rik      0      0 1.43484e+11      0     0     0
9330159M07Rik      0      0 1.43484e+11      0     0     0
Ak9                0      0 1.43484e+11      0     0     0

head(colData)
       condition
BM12_1   inflamm
BM12_2   inflamm
Treg_1      Treg
Treg_2      Treg
Con_1       none
Con_2       none
all(rownames(colData) %in% colnames(countData))
[1] TRUE
countData <- countData[, rownames(colData)]
all(rownames(colData) == colnames(countData))
[1] TRUE
library ("DESeq2")

Lade nötiges Paket: S4Vectors
Lade nötiges Paket: stats4
Lade nötiges Paket: BiocGenerics
Lade nötiges Paket: parallel

Attache Paket: ‘BiocGenerics’

The following objects are masked from ‘package:parallel’:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ, clusterExport, clusterMap, parApply, parCapply, parLapply, parLapplyLB,
    parRapply, parSapply, parSapplyLB

The following objects are masked from ‘package:stats’:

    IQR, mad, xtabs

The following objects are masked from ‘package:base’:

    anyDuplicated, append, as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq, Filter, Find, get, grep, grepl, intersect,
    is.unsorted, lapply, lengths, Map, mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank, rbind, Reduce,
    rownames, sapply, setdiff, sort, table, tapply, union, unique, unsplit, which, which.max, which.min


Attache Paket: ‘S4Vectors’

The following objects are masked from ‘package:base’:

    colMeans, colSums, expand.grid, rowMeans, rowSums

Lade nötiges Paket: IRanges
Lade nötiges Paket: GenomicRanges
Lade nötiges Paket: GenomeInfoDb
Lade nötiges Paket: SummarizedExperiment
Lade nötiges Paket: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with 'browseVignettes()'. To cite Bioconductor, see 'citation("Biobase")', and for
    packages 'citation("pkgname")'.

dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~ condition)
converting counts to integer mode
Fehler in if (all(assay(se) == 0)) { : 
  Fehlender Wert, wo TRUE/FALSE nötig ist
Zusätzlich: Warnmeldung:
In `mode<-`(`*tmp*`, value = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,  :
  NAs introduced by coercion to integer range




sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 10586)

locale:
[1] LC_COLLATE=German_Germany.1252  LC_CTYPE=German_Germany.1252    LC_MONETARY=German_Germany.1252 LC_NUMERIC=C                   
[5] LC_TIME=German_Germany.1252    

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

other attached packages:
[1] DESeq2_1.14.1              SummarizedExperiment_1.4.0 Biobase_2.34.0             GenomicRanges_1.26.1       GenomeInfoDb_1.10.1       
[6] IRanges_2.8.1              S4Vectors_0.12.1           BiocGenerics_0.20.0       

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.8          RColorBrewer_1.1-2   plyr_1.8.4           XVector_0.14.0       bitops_1.0-6         tools_3.3.2          zlibbioc_1.20.0     
 [8] digest_0.6.10        rpart_4.1-10         base64_2.0           memoise_1.0.0        RSQLite_1.1-1        annotate_1.52.0      tibble_1.2          
[15] gtable_0.2.0         htmlTable_1.7        lattice_0.20-34      Matrix_1.2-7.1       DBI_0.5-1            gridExtra_2.2.1      genefilter_1.56.0   
[22] stringr_1.1.0        cluster_2.0.5        knitr_1.15.1         locfit_1.5-9.1       grid_3.3.2           nnet_7.3-12          data.table_1.10.0   
[29] AnnotationDbi_1.36.0 XML_3.98-1.5         survival_2.40-1      BiocParallel_1.8.1   foreign_0.8-67       latticeExtra_0.6-28  Formula_1.2-1       
[36] geneplotter_1.52.0   ggplot2_2.2.0        magrittr_1.5         htmltools_0.3.5      Hmisc_4.0-1          scales_0.4.1         splines_3.3.2       
[43] assertthat_0.1       xtable_1.8-2         colorspace_1.3-2     stringi_1.1.2        acepack_1.4.1        RCurl_1.95-4.8       lazyeval_0.2.0      
[50] openssl_0.9.5        munsell_0.4.3       
>

Answer 1

[Michael Love]

Feel free to post to Bioconductor support site (it's identical to this one except all the Bioconductor maintainers are registered, so we get notifications for relevant messages).

Something seems wrong with your counts: 1.43484e+11

That's a big count, yeah?