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  • cuffdiff for differential gene testing

    Hello,
    I am using tophat, cufflinks, cuffcompare and cuffdiff to analyze 5 MZ twin pairs discordant for diabetes.
    After the preliminary fastq groomer file conversion, the RNA-seq fastq paired end data files are run in tophat with reference HG19 genome to align the reads.
    Cuffcompare is then run on the tophat files to compare twin pair transcripts.
    Finally, cuffdiff is used first to compare individual twin pairs (tophat files)
    with HG19 reference gtf which, generates unique NM ids, FPKM values, p
    and q statistic values and fdr significances.
    Then the groups replicate function is used to the combined diabetic and non-diabetic twins in 2 groups against the HG19 reference gtf.
    This also, produces NM ids, etc.
    From my reading of the documentation it appears the statistical test for replicates is similar a group comparison t-test. What I would like to run is a
    combined paired t-test as the samples are MZ twins. I think I am ok with the
    initial individual twins cuffdiff analysis but, suspect the combined replicates
    is a group mean comparison rather then a combined paired comparison.
    The documentation on cufflinks says not to use count-based differential gene
    methods on the FPKM data. I am not sure this applies to the data after cuffdiff analyses as the spliced variants are separated after this analysis but, when I run a paired t-test on the extracted FPKM 5 twin pairs data I get quite different results.
    What is going on?

    Paul W.

  • #2
    answer for the same

    Dear Sir,

    Have you managed to get answer for this. We are looking for answer of similar question.

    Thank you,
    Mudita

    Comment


    • #3
      paired t-test and differential gene testing

      What I did was to use a 3rd party software called Gene Data Expressionist.
      The GDE Genome Refiner module can be used with Tophat alignment bam or sam files. There are defined workflows for RNA-seq to do the transcript counting and generate FPKM normalized counts that can be used for statistical comparison testing.

      Comment


      • #4
        Dear all,

        I have some output files from two rna seq conditions. e.g.
        genes.fpkm.tracking
        isoforms.fpkm.tracking
        transcripts.gtf

        Since I am new in rna seq analysis and I am kind of lost. I will highly appreciate if I could get an idea where should i start to interpret these output files.

        Thanks.
        Adeel
        Last edited by adeel_malik; 03-11-2013, 06:17 PM.

        Comment


        • #5
          Hi Paul

          I was wondering whether you have published anything with this RNAseq data you have? Is the data publicly available yet>?


          Cheers,
          Matt

          Comment

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