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       
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