Hi,

I'm trying to use DESeq2 to analyse a dataset where I've generated abundances using Kallisto following the vignette "Analyzing RNA-seq data with DESeq2".

I'm getting a consistent error with DESeqDataSetFromTximport:

> dds <- DESeqDataSetFromTximport(txi.kallisto, samples, ~condition)
Error in validObject(.Object) :
  invalid class “SummarizedExperiment” object: 1: invalid object for slot "NAMES" in class "SummarizedExperiment": got class "array", should be or extend class "character_OR_NULL"
invalid class “SummarizedExperiment” object: 2: 'names(x)' must be NULL or a character vector with no attributes

The same error occurs if you just take counts:

counts <- as.matrix(txi.kallisto$counts)

and then use DESeqDataSetFromMatrix.

Gone through this systematically and found that there's an issue with the rownames of the counts table within the tximport list, it looks like it is setting them as arrays?

> class(rownames(counts))
[1] "array"

Which then if I set them as a character it seems to accept the matrix (if I round the counts as in the fromTximport function). I can now fix the txi list by doing this:

> rownames(txi.kallisto$counts) <- as.character(rownames(txi.kallisto$counts))

> dds <- DESeqDataSetFromTximport(txi.kallisto, samples, ~condition)
using counts and average transcript lengths from tximport

This now appears to work. I think that this must just be a slight bug from one part of the workflow?

Session info below, I updated to the dev version of DESeq2 to see if that fixed it but the same error was in the main release.

> sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.5 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.0
LAPACK: /usr/lib/lapack/liblapack.so.3.0

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

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

other attached packages:
 [1] DESeq2_1.17.2              SummarizedExperiment_1.6.3 DelayedArray_0.2.7         matrixStats_0.52.2        
 [5] Biobase_2.36.2             GenomicRanges_1.28.3       GenomeInfoDb_1.12.2        IRanges_2.10.2            
 [9] S4Vectors_0.14.3           BiocGenerics_0.22.0        tximport_1.4.0            

loaded via a namespace (and not attached):
 [1] genefilter_1.58.1       locfit_1.5-9.1          rhdf5_2.20.0            splines_3.4.0           lattice_0.20-35        
 [6] colorspace_1.3-2        htmltools_0.3.6         base64enc_0.1-3         survival_2.41-3         XML_3.98-1.7           
[11] rlang_0.1.1             DBI_0.6-1               foreign_0.8-68          BiocParallel_1.10.1     RColorBrewer_1.1-2     
[16] GenomeInfoDbData_0.99.0 plyr_1.8.4              stringr_1.2.0           zlibbioc_1.22.0         munsell_0.4.3          
[21] gtable_0.2.0            htmlwidgets_0.8         memoise_1.1.0           latticeExtra_0.6-28     knitr_1.16             
[26] geneplotter_1.54.0      AnnotationDbi_1.38.1    htmlTable_1.9           Rcpp_0.12.11            acepack_1.4.1          
[31] xtable_1.8-2            scales_0.4.1            backports_1.1.0         checkmate_1.8.2         Hmisc_4.0-3            
[36] annotate_1.54.0         XVector_0.16.0          gridExtra_2.2.1         ggplot2_2.2.1           digest_0.6.12          
[41] stringi_1.1.5           grid_3.4.0              tools_3.4.0             bitops_1.0-6            magrittr_1.5           
[46] RSQLite_1.1-2           lazyeval_0.2.0          RCurl_1.95-4.8          tibble_1.3.3            Formula_1.2-1          
[51] cluster_2.0.6           Matrix_1.2-10           data.table_1.10.4       rpart_4.1-11            nnet_7.3-12            
[56] compiler_3.4.0        

I also found this problem when I import abundance.h5 of kallisto using tximport (1.4.0). Change the class of target_id from array to character in function read_kallisto_h5 [line 42 of helper.R] can fix my problem.

target_id = as.character(ids)

# code contributed from Andrew Morgan
read_kallisto_h5 <- function(fpath, ...) {
  if (!requireNamespace("rhdf5", quietly=TRUE)) {
    stop("reading kallisto results from hdf5 files requires Bioconductor package `rhdf5`")
  }
  counts <- rhdf5::h5read(fpath, "est_counts")
  ids <- rhdf5::h5read(fpath, "aux/ids")
  efflens <- rhdf5::h5read(fpath, "aux/eff_lengths")

  stopifnot(length(counts) == length(ids)) 
  stopifnot(length(efflens) == length(ids))

  result <- data.frame(target_id = as.character(ids),
                       eff_length = efflens,
                       est_counts = as.numeric(counts),
                       stringsAsFactors = FALSE)
  normfac <- with(result, (1e6)/sum(est_counts/eff_length))
  result$tpm <- with(result, normfac*(est_counts/eff_length))
  return(result)
}

I also checked the difference of txi objects from tsv and h5. Notice [1:178136(1d)] in txi.kallisto.

library("tximport")
library("readr")
library("tximportData")
dir <- system.file("extdata", package="tximportData")
samples <- read.table(file.path(dir,"samples.txt"), header=TRUE)
samples$condition <- factor(rep(c("A","B"),each=3))
rownames(samples) <- samples$run
samples[,c("pop","center","run","condition")]
tx2gene <- read.csv(file.path(dir, "tx2gene.csv"))

files <- file.path(dir, "kallisto_boot", samples$run, "abundance.h5")
names(files) <- paste0("sample", 1:6)
txi.kallisto <- tximport(files, type = "kallisto", txOut = TRUE, dropInfReps = TRUE)
#rownames(txi.kallisto$counts) <- as.character(rownames(txi.kallisto$counts))
head(txi.kallisto$counts)

files <- file.path(dir, "kallisto", samples$run, "abundance.tsv")
names(files) <- paste0("sample", 1:6)
txi.kallisto.tsv <- tximport(files, type = "kallisto", tx2gene = tx2gene)
head(txi.kallisto.tsv$counts)

> str(txi.kallisto)
List of 4
 $ abundance          : num [1:178136, 1:6] 0 0 0 0 0 0 0 0 0 0 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:178136(1d)] "ENST00000448914.1" "ENST00000631435.1" "ENST00000632684.1" "ENST00000434970.2" ...
  .. ..$ : chr [1:6] "sample1" "sample2" "sample3" "sample4" ...
 $ counts             : num [1:178136, 1:6] 0 0 0 0 0 0 0 0 0 0 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:178136(1d)] "ENST00000448914.1" "ENST00000631435.1" "ENST00000632684.1" "ENST00000434970.2" ...
  .. ..$ : chr [1:6] "sample1" "sample2" "sample3" "sample4" ...
 $ length             : num [1:178136, 1:6] 7.75 6.75 6.75 5.67 4.67 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:178136(1d)] "ENST00000448914.1" "ENST00000631435.1" "ENST00000632684.1" "ENST00000434970.2" ...
  .. ..$ : chr [1:6] "sample1" "sample2" "sample3" "sample4" ...
 $ countsFromAbundance: chr "no"

> str(txi.kallisto.tsv)
List of 4
 $ abundance          : num [1:25343, 1:6] 3.8408 2.7673 0.0798 0.3727 0.0367 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:25343] "A1BG" "A1BG-AS1" "A1CF" "A2M" ...
  .. ..$ : chr [1:6] "sample1" "sample2" "sample3" "sample4" ...
 $ counts             : num [1:25343, 1:6] 108.6 86.2 9 24 1 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:25343] "A1BG" "A1BG-AS1" "A1CF" "A2M" ...
  .. ..$ : chr [1:6] "sample1" "sample2" "sample3" "sample4" ...
 $ length             : num [1:25343, 1:6] 1939 2136 7737 4417 1869 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:25343] "A1BG" "A1BG-AS1" "A1CF" "A2M" ...
  .. ..$ : chr [1:6] "sample1" "sample2" "sample3" "sample4" ...
 $ countsFromAbundance: chr "no"