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  • tophat:all p-value are greater than 5e-05 ??

    Hello all,

    when I plot my data by cummeRbund with the function
    > v<-csVolcanoMatrix(genes(cuff))
    > v

    the plot showed all p-value are greater than 5e-05.
    But I could not find how I get this. Please help me, Thanks a lot!
    Attached Files

  • #2
    From the CummeRbund help page:

    Code:
    > gene.diff<-diffData(genes(cuff))
    > head(gene.diff)
     
    
          gene_id sample_1 sample_2 status   value_1     value_2
    1 XLOC_000001      iPS     hESC NOTEST  20.21750 3.47386e-01
    2 XLOC_000002      iPS     hESC NOTEST   0.00000 0.00000e+00
    3 XLOC_000003      iPS     hESC NOTEST   0.00000 0.00000e+00
    4 XLOC_000004      iPS     hESC     OK   0.00000 6.97259e+05
    5 XLOC_000005      iPS     hESC     OK 355.82300 6.96704e+02
    6 XLOC_000006      iPS     hESC NOTEST   1.51396 0.00000e+00
      log2_fold_change     test_stat    p_value    q_value
    1     -5.86292e+00   7.13525e-01 0.47552100 1.00000000
    2      0.00000e+00   0.00000e+00 1.00000000 1.00000000
    3      0.00000e+00   0.00000e+00 1.00000000 1.00000000
    4     1.79769e+308  1.79769e+308 0.00857693 0.02109120
    5      9.69385e-01  -2.98373e+00 0.00284757 0.00840284
    6    -1.79769e+308 -1.79769e+308 0.24382400 1.00000000
      significant
    1          no
    2          no
    3          no
    4         yes
    5         yes
    6          no
    So gene.diff$q_value should hold the values to use.

    Comment


    • #3
      Originally posted by dpryan View Post
      From the CummeRbund help page:

      Code:
      > gene.diff<-diffData(genes(cuff))
      > head(gene.diff)
       
      
            gene_id sample_1 sample_2 status   value_1     value_2
      1 XLOC_000001      iPS     hESC NOTEST  20.21750 3.47386e-01
      2 XLOC_000002      iPS     hESC NOTEST   0.00000 0.00000e+00
      3 XLOC_000003      iPS     hESC NOTEST   0.00000 0.00000e+00
      4 XLOC_000004      iPS     hESC     OK   0.00000 6.97259e+05
      5 XLOC_000005      iPS     hESC     OK 355.82300 6.96704e+02
      6 XLOC_000006      iPS     hESC NOTEST   1.51396 0.00000e+00
        log2_fold_change     test_stat    p_value    q_value
      1     -5.86292e+00   7.13525e-01 0.47552100 1.00000000
      2      0.00000e+00   0.00000e+00 1.00000000 1.00000000
      3      0.00000e+00   0.00000e+00 1.00000000 1.00000000
      4     1.79769e+308  1.79769e+308 0.00857693 0.02109120
      5      9.69385e-01  -2.98373e+00 0.00284757 0.00840284
      6    -1.79769e+308 -1.79769e+308 0.24382400 1.00000000
        significant
      1          no
      2          no
      3          no
      4         yes
      5         yes
      6          no
      So gene.diff$q_value should hold the values to use.
      Thanks dpryan! But I'm sorry, I did not get the meaning 'gene.diff$q_value should hold the values to use', could you explain more details please?

      Comment


      • #4
        Hi spreefu,

        My understanding is that you're trying to extract the p-values (or probably more useful, the q-value) from your dataset. These are available using the "diffData" function which returns a data.frame (the top portion of example output was provided in my earlier reply). This data.frame contains the p and q-values that you seem to be looking for. If you just want to double check that the lowest p-value is > 5e-5, then just:

        Code:
        gene.diff<-diffData(genes(cuff))
        min(gene.diff$p_value)
        The "$p_value" just says, "just look at the column labeled p_value". You'll find a basic fluency in R to be very helpful in bioinformatics, so I would recommend going through a few tutorials (or taking a class if there's one offered locally).

        Comment


        • #5
          Originally posted by dpryan View Post
          Hi spreefu,

          My understanding is that you're trying to extract the p-values (or probably more useful, the q-value) from your dataset. These are available using the "diffData" function which returns a data.frame (the top portion of example output was provided in my earlier reply). This data.frame contains the p and q-values that you seem to be looking for. If you just want to double check that the lowest p-value is > 5e-5, then just:

          Code:
          gene.diff<-diffData(genes(cuff))
          min(gene.diff$p_value)
          The "$p_value" just says, "just look at the column labeled p_value". You'll find a basic fluency in R to be very helpful in bioinformatics, so I would recommend going through a few tutorials (or taking a class if there's one offered locally).
          Hi dpryan,
          Thanks for your suggestion! I know if I want to find the significant genes, I should take q-value.
          But I still have the question about those p-values in my data. Because p-values of many genes are 5e-5, it seems 5e-5 is a limit here. Then when I generate the volcano-plot, you can see my picture attach in the first post, it looks the volcano was cut by a line.
          If you have look in cummeRbund manual here:

          the p-value in their volcano-plot do not limit by 5e-5. This is what I wondered.
          Thanks!

          Comment


          • #6
            Hi dpryan,

            Thanks for your help! Sorry for confusing you because of I did not describe my question clearly at first.
            For the question here 'But I still have the question about those p-values in my data. Because p-values of many genes are 5e-5, it seems 5e-5 is a limit here. Then when I generate the volcano-plot, you can see my picture attached in the first post, it looks the volcano was cut by a line.
            If you have look in cummeRbund manual here:

            the p-value in their volcano-plot do not limit by 5e-5. This is what I wondered.' Do you have any idea?

            Comment


            • #7
              The p-values come from cuffdiff, but unfortunately I don't know enough about its inner-workings to give you a good answer to that.

              Comment


              • #8
                Originally posted by dpryan View Post
                The p-values come from cuffdiff, but unfortunately I don't know enough about its inner-workings to give you a good answer to that.
                Anyway, still thanks a lot! Schönes Wochenende!

                Comment


                • #9
                  In the thread http://http://seqanswers.com/forums/...ad.php?t=30705
                  just mentioned that, hope it helps

                  Comment


                  • #10
                    hi yzzhang, thanks for your help!

                    Comment

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