Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • NDUFB11
    Member
    • Jul 2017
    • 34

    #1

    error in DESeqDataSet

    Dear all,

    I have 4 RNAseq file from an experiment with two different conditions,
    "Untreated" and "Treated" and after thee counting of the reads with futureCounts I'm trying to analyze it with DESeq2, here the command lines

    Code:
    countdata <- as.matrix(read.table("'/DESeq2_STAR/count.table", header=TRUE, row.names=1))
    head (countdata)
    condition <- factor(c(rep("Untreated",2), rep("Treated",2)))
    coldata <- data.frame(row.names=colnames(countdata),condition)
    head(coldata)
    library("DESeq2")
    dds <- DESeqDataSetFromMatrix(countdata, coldata, design=~condition)

    everything is ok until the last command line,


    Code:
    > dds <- DESeqDataSetFromMatrix(countdata, coldata, design=~condition)
    Error in DESeqDataSet(se, design = design, ignoreRank) : 
      some values in assay are not integers

    I don't understand what is not integers?
    My table look similar to those describe in DESeq2 vignettes

    Code:
                mapping.star.PF382 mapping.star.SUPT1 mapping.star.SUPT13 mapping.star.RPMI8402
    ENSG00000223972               7.12             119.48               27.45                 58.49
    ENSG00000227232            2793.80            2410.36             1630.14               2960.74
    ENSG00000243485              30.00               2.93               20.52                 16.32
    ENSG00000237613               0.00               0.00                1.83                  1.00
    ENSG00000268020               1.00               0.00                0.50                  0.00
    ENSG00000240361               0.00               0.00                0.00                  0.00
    Thank you

Latest Articles

Collapse

  • SEQadmin2
    16S/ITS Profiling vs. Shotgun Metagenomics: What Changes in Your Workflow?
    by SEQadmin2




    NGS has revolutionized clinical microbiology by offering new ways to identify and surveil pathogens without prior knowledge of the target. One popular approach is 16S rRNA and ITS amplicon sequencing, which targets specific microbial markers. But studies are increasingly incorporating shotgun metagenomics, a technique that sequences all DNA from a sample without targeting specific microbial markers. This approach allows more detailed taxonomic classification, detection...
    Today, 06:46 AM
  • SEQadmin2
    Multiomic Liquid Biopsy: What DNA/RNA Panels Reveal That DNA Alone Can’t
    by SEQadmin2



    Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?

    Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating
    ...
    10-14-2026, 09:55 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by SEQadmin2, 10-28-2026, 09:57 AM
0 responses
24 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 10-28-2026, 09:51 AM
0 responses
15 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 10-22-2026, 11:13 AM
0 responses
71 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 10-22-2026, 10:48 AM
0 responses
48 views
0 reactions
Last Post SEQadmin2  
Working...