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  • Output count table in DESeq 2

    Hello all,

    I am trying to output the count table that is created to be used for differential expression analysis in DESeq. I'm just having trouble on what code to use to get a tab-delimited text file with Gene_ID as row headers and replicates as column headers.
    This is what I have so far. Could this be done in HTSeq-count?
    Code:
    library("DESeq2")
    
    files = c("merged_sample_2.bam_htseq_out.txt","merged_sample_11.bam_htseq_out.txt","merged_sample_20.bam_htseq_out.txt","merged_sample_3.bam_htseq_out.txt","merged_sample_12.bam_htseq_out.txt","merged_sample_21.bam_htseq_out.txt")
    
    cond = c("GFP","GFP","GFP","DBM","DBM","DBM")
    
    sTable = data.frame(sampleName = files, fileName = files, condition = cond)
    
    dds <-DESeqDataSetFromHTSeqCount(sampleTable=sTable, directory = "/Volumes/cachannel/RNA_SEQ/Notch_RNASeq/in_silico_test/DESeq", design = ~condition)
    I am planning on using this count table with a tool called Scotty - "a tool to assist in the designing of RNA Seq experiments that have adequate power to detect differential expression at the level required to achieve experimental aims" Check it out here: http://scotty.genetics.utah.edu/

    Thanks

  • #2
    Do I understand it correctly that you haven't used htseq-count up to this point?

    Comment


    • #3
      I have used htseq-count, I even have the count files from that but I would like to put that in a tab delimited text file.

      Comment


      • #4
        The function DESeqDataSetFromHTSeqCount should be perfectly able to read in the separate htseq-count files. Using this link you can find some pointers: http://rpackages.ianhowson.com/bioc/...eqDataSet.html

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        • #5
          Thanks! I understand how this works - just having trouble outputting the table in a tab delimited text file. Any help on that? I even have tried to output the count table in a csv format using write.csv(), but ran into an error.

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          • #6
            you can access the counts from the dds object by using the counts <- assay(dds) function if I'm not terribly mistaken

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            • #7
              Okay, I think i've got it. Thank you very much!

              Comment

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