Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • DESeq2 LRT insights

    Hi,
    We're working on a RNA binding protein and want to figure out if it binds different RNAs in 2 different conditions. We did an immunoprecipitation (IP) for the protein and prepared the RNA that was linked to the protein for sequencing. Eventually we have 4 libraries: total RNA in condition A, RNAs in IP in condition A, total in condition B and IP in condition B.
    I want to know which RNAs are more (or less) in the IP in condition A vs. B normalized by the total RNA in these conditions. I used LRT of DESeq2 like this:
    ddseq <- DESeq(ddseq, test="LRT", full=~group+condition, reduced=~group)
    where group is IP and total and condition is condition A and B. This should tell me if the condition influence the ratio between IP and Total.
    What I'm missing is the size of the effect. I can get the p-value from the results but I couldn't figure out how to see the effect of condition a vs B on the IP/Total. I'd appreciate your help.
    Thanks

  • #2
    hi Asaf,

    The effect size is the column log2FoldChange in the results table. You can get more information on columns in the results table by inspecting the metadata columns:

    mcol(res, use.names=TRUE)

    Comment


    • #3
      Thanks Mike, it's much clearer now.
      However, after doing some thinking since I wrote the first post I now think that the formula should be:
      full=~group+condition+group:condition, reduced=~group+condition
      if I really want to test if the condition has an effect on IP/Total. Am I correct?

      Comment


      • #4
        Yes, sorry I skimmed the original post and just answered the question about the results table. You're right that you need to fit an interaction model and test the interaction term in order to test the ratio of ratios: IP/control / IP/control.

        But it appears you don't have biological replicates to fit the model with an interaction. The model with an interaction has four terms:

        intercept + group effect + condition effect + group:condition effect

        And you have only 4 samples if I read correctly. So there are no residual degrees of freedom to estimate the within-group variance. Is it possible to perform more replicates of some groups in the experiment to observe the variability within group and condition? At the least you could replicate one or both of the IPs?

        Comment


        • #5
          Thanks again,
          We have 2 replicates of all 4 libraries so we should have enough, I do get significant genes (13) and some of them even makes sense biologically .

          Comment

          Latest Articles

          Collapse

          • seqadmin
            Strategies for Sequencing Challenging Samples
            by seqadmin


            Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
            03-22-2024, 06:39 AM
          • seqadmin
            Techniques and Challenges in Conservation Genomics
            by seqadmin



            The field of conservation genomics centers on applying genomics technologies in support of conservation efforts and the preservation of biodiversity. This article features interviews with two researchers who showcase their innovative work and highlight the current state and future of conservation genomics.

            Avian Conservation
            Matthew DeSaix, a recent doctoral graduate from Kristen Ruegg’s lab at The University of Colorado, shared that most of his research...
            03-08-2024, 10:41 AM

          ad_right_rmr

          Collapse

          News

          Collapse

          Topics Statistics Last Post
          Started by seqadmin, 03-27-2024, 06:37 PM
          0 responses
          12 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 03-27-2024, 06:07 PM
          0 responses
          11 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 03-22-2024, 10:03 AM
          0 responses
          53 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 03-21-2024, 07:32 AM
          0 responses
          68 views
          0 likes
          Last Post seqadmin  
          Working...
          X