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  • unique379
    Member
    • Aug 2012
    • 27

    miRNA and DESeq

    Hello all,

    Just a quick answer by experts
    I am dealing with miRNA-seq data and having some doubt.
    1) Filtering by resSig <- res[ res$padj < .1, ]
    I am not able to get any significant miRNAs on my sample while by using
    resSig <- res[ res$pval < 0.05, ]
    i am getting about 41 DE miRNAs (up and down)…

    what should i do ??? may i rigid with only pval makes sense ??? I mean "i just keep going only filtering by pval < 0.05, is that enough to consider my genes significantly differentially expressed? "

    2) after this analysis may go further for filtering by overall counts, plotting Heat map and PCA plots would be good results ??? This makes any significant sense ?? I am asking because, i am not very expert in statistics.

    Thanks, any help would be appreciated
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    Cross-posted on biostars. As I mentioned there:

    I wouldn't use unadjusted p-values unless really desperate (they're less likely to validate). If you haven't done so already, try doing some independent filtering to increase statistical power.

    Comment

    • unique379
      Member
      • Aug 2012
      • 27

      #3
      Originally posted by dpryan View Post
      Cross-posted on biostars. As I mentioned there:



      Thanks for your suggestion but could you please explore your advice. As i am not so expert of R

      Comment

      • dpryan
        Devon Ryan
        • Jul 2011
        • 3478

        #4
        I've replied over on biostars since the thread there is getting a bit more traffic.

        Comment

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