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  • scottdaniel
    Junior Member
    • Apr 2012
    • 9

    Read runs and technical replicates

    So I've downloaded some example data from SRA archives at http://www.ncbi.nlm.nih.gov/sra?term=SRA011001 and had a question about technical and biological replicates (see attached picture for a snapshot of the downloads). I know that there are two biological replicates for control and treatment conditions (in this case a miR155 over-expression retrovirus) but I'm not sure about the technical replicates.

    Do read runs count as technical replicates?

    And, if so, how can I use that in my analysis pipeline (currently I'm using the Tuxedo suite (i.e. tophat > cufflinks > cuffmerge, etc.)).

    Right now I think I'm just telling the program that there are six biological replicates of each condition (i.e. 6 x miR155oe vs. 6 x control) which is probably wrong.

    Thanks, Scott
    Attached Files
  • chadn737
    Senior Member
    • Jan 2009
    • 392

    #2
    It has been shown in many cases that Biological variation is far greater than technical variation in Illumina sequencing and typically individual runs are pooled together and treated as one sample. Ideally thats why you multiplex all your biological replicates and spread the sequencing across multiple lanes.

    Comment

    • scottdaniel
      Junior Member
      • Apr 2012
      • 9

      #3
      Originally posted by chadn737 View Post
      It has been shown in many cases that Biological variation is far greater than technical variation in Illumina sequencing and typically individual runs are pooled together and treated as one sample. Ideally thats why you multiplex all your biological replicates and spread the sequencing across multiple lanes.
      Is there paper where this is shown?

      So perhaps I should merge my .sam files per biological replicate and then do the tophat/bowtie alignment?

      Thanks.

      Comment

      • chadn737
        Senior Member
        • Jan 2009
        • 392

        #4
        Marioni, J. C., C. E. Mason, S. M. Mane, M. Stephens and Y. Gilad,
        2008 RNA-Seq: an assessment of technical reproducibility and
        comparison with gene expression arrays. Genome Res. 18: 1509–1517.

        Comment

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