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  • federete
    Junior Member
    • Feb 2013
    • 2

    RNA-seq and GC content bias

    Dear all,

    I am analyzing a dataset of RNA-seq (from Illumina Genome Analyser IIx), and have found some interesting expression pattern trends related to the GC content of genes. After reading the literature, I have noticed that RNA-seq has some biases related to the GC content. Hence, I am not sure of the validity of my inferences.

    So, my question, or questions are:
    -How can I determine if this is a biologically meaningful trend or rather so a bias of the methodology?
    -To what extent does the GC content biases the results of RNA-seq experiments? (the "trends" that I observe are strong)
    -I am working with published RPKM values, and was wondering if I need to recalculate all these values considering GC content biases or if I could just test how much bias is in the data.

    Any clue with any of these questions is highly appreciated!
    Federico
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    Have a look at the conditional quantile normalization paper from Hansen et al. (http://biostatistics.oxfordjournals..../13/2/204.full). I expect that has much of what you're looking for.

    Comment

    • federete
      Junior Member
      • Feb 2013
      • 2

      #3
      Many thanks, dpryan

      I am not sure whether I could guess from the paper the extent of the influence of the GC content, but will do some tests with my data to see what can I see

      Fede

      Comment

      • amcloon
        Member
        • Sep 2012
        • 15

        #4
        This was also a concern of mine since I work with a GC-rich species, and it is clear from Aird et al, 2011 (Genome Biology 12:R18) that PCR conditions during library prep can non-uniformly amplify transcripts with different GC contents. If you are really seeing systematic biases, I would figure out what you did/had done during library construction (polymerase, buffers, etc.), to know if you can anticipate that you had biased amplification.

        I am not sure this will help your analysis any, but at least if your preparation didn't take this into account, you can write off some of the variability that way.

        Anna

        Comment

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