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  • RNA-seq bio-replication with low correlation

    Hi!
    I sequeced two biological replicates for one condition with Hiseq 2000 platfom.
    but the typical R(Pearson) correlation of gene expression(Raw Count) between two biological replicates is only 0.93, ie the R2 only about 0.87.
    Can I use these 2 samples to do the differencial analysis?
    Any suggestion for how to use this to call DE genes?
    Or some recommend readings are also very helpful.

    Thanks all.

  • #2
    Sure, that's certainly a high enough correlation (to be frank, I wouldn't bother calculating that, just cluster the samples).

    For calling DE genes, give DESeq2 or edgeR or limma/voom a try.

    Comment


    • #3
      Originally posted by dpryan View Post
      Sure, that's certainly a high enough correlation (to be frank, I wouldn't bother calculating that, just cluster the samples).

      For calling DE genes, give DESeq2 or edgeR or limma/voom a try.
      hi dpryan,
      thank you for your reply,
      I have read an artical for rnaseq written by ENCODE (the title is Standards, Guidelines and Best Practices for RNA-Seq),and they suguest that "A typical R2(Pearson) correlation of gene expression(RPKM) between two biological replicates, for RNAs that are detected in both samplesusing RPKM orread counts, should be between 0.92 to 0.98. Experiments with biological correlations that fall below 0.9 should be either be repeated or explained."
      so I am very abset about my data. are you sure about R=0.93 is high enough for RNAseq? then I can go on my work.
      thanks.

      Comment


      • #4
        Note firstly that they talk about RPKM correlation, which will be different from raw counts.

        Secondly, ENCODE's recommendations are just that, recommendations. That don't apply to every experiment and will often be useless in a given circumstance (and anyway, your correlation coefficient is in the range mentioned). Keep in mind also that they mostly use cell lines, so if you have different source material then such a high correlation might be impossibly high.

        Comment


        • #5
          oh, I see,
          thank you very much!

          Comment

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