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  • john_nl
    Member
    • Feb 2012
    • 13

    Combining FPKM values for a gene

    Hello,

    Hopefully this is a simple question that gets a simple answer:

    I just want to map my reads using bowtie to a well defined transcriptome in the form of a cDNA library. This works very nicely, but the problem is that after running it through cufflinks, it gives FPKM values for each transcript isoform that correspond to one gene. Essentially, I want one "score" for each gene- can i just sum FPKM values for each isoform for a given gene?

    ta
  • adamdeluca
    Member
    • Jul 2010
    • 95

    #2
    You can use the -G option to force cufflinks to only estimate expression of the reference transcripts you supply. Supply 1/gene.

    Comment

    • kopi-o
      Senior Member
      • Feb 2008
      • 319

      #3
      You should be able to just sum the FPKMs.

      Comment

      • Simon Anders
        Senior Member
        • Feb 2010
        • 995

        #4
        ARe you sure that cufflinks likes to work on data aligned to the [I]transcriptome[/I[? I suppose you mean by this that you supplied bowtie not with FASTA files for the genome but with files for the tranmscripts. This does not sound like the workflow it is designed for.

        In any case, if you just want to know the expression strength of the genes, would it not be easier to count how many reads fall onto any exon of a given gene, rather than letting cuffdiff deconvolute this into transcripts, and you sum this up again.

        Comment

        • natstreet
          Member
          • Nov 2009
          • 83

          #5
          If you are mapping directly to a transcriptome I would maybe suggest trying RSEM and supplying it with a FASTA file of reference transcripts containing only one isoform per gene. The RSEM paper is here and the website here. RSEM is an R package that uses bowtie as a read mapper by default.

          Comment

          • john_nl
            Member
            • Feb 2012
            • 13

            #6
            Thank you very much for all of your answers. Much appreciated.

            Comment

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