Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Help with how to interpret density plot (cummeRbund)

    Dear all,

    I am analyzing my 50bp paired-end RNA-seq using the Tophat - Cuffdiff - Cufflinks - cummeRbund pipeline.

    I am a little confused on how to interpret the density plot I get from one experiment, where I am comparing ESC, Haploid and Diploid cells.
    For the RP sample, I do not see this bimodal distribution, as I see for the other samples.



    Is it something I should worry about? I have kind of same shape with another couple of samples from white adipose tissue. My boss flags the normalization as crap as soon as he doesnt see the bimodal distribution, but I am not really sure if it really has to be bimodal. What are your thoughts on this?

    The fastqc files pass the fastQC quality controls.

    Thanks in advance. Appreciate all inputs!

  • #2
    Did you get the answer ?
    If yes, can you explain me please ?
    Thanks

    Comment


    • #3
      Hi
      I got something for you but not very useful.

      commands:
      # this will generate same figure as yours
      > csDensity(genes(cuff_data), logMode=TRUE, pseudocount= 0, features=FALSE, replicates=FALSE)
      # try changing pseudocount = ? i.e 1 to 0.000001 to -1
      csDensity(genes(cuff_data), logMode=TRUE, pseudocount= -1, features=FALSE, replicates=FALSE)

      you can get the results as you want. But I dont know if it is the way to do it and not sure how to explain it. I just tried.
      Do reply plz



      Originally posted by DonDolowy View Post
      Dear all,

      I am analyzing my 50bp paired-end RNA-seq using the Tophat - Cuffdiff - Cufflinks - cummeRbund pipeline.

      I am a little confused on how to interpret the density plot I get from one experiment, where I am comparing ESC, Haploid and Diploid cells.
      For the RP sample, I do not see this bimodal distribution, as I see for the other samples.



      Is it something I should worry about? I have kind of same shape with another couple of samples from white adipose tissue. My boss flags the normalization as crap as soon as he doesnt see the bimodal distribution, but I am not really sure if it really has to be bimodal. What are your thoughts on this?

      The fastqc files pass the fastQC quality controls.

      Thanks in advance. Appreciate all inputs!

      Comment


      • #4
        No, I never got an explanation but since I posted here I have analyzed data from many other experiments, where I usually do not run see such a density plot.

        Comment


        • #5
          You may try it out my above commands and you will get normalised good view.
          If you need more info about heatmap and color change and incuding dandogram such thing, plz do reply
          Thank you

          Originally posted by DonDolowy View Post
          No, I never got an explanation but since I posted here I have analyzed data from many other experiments, where I usually do not run see such a density plot.

          Comment

          Latest Articles

          Collapse

          • seqadmin
            Essential Discoveries and Tools in Epitranscriptomics
            by seqadmin


            The field of epigenetics has traditionally concentrated more on DNA and how changes like methylation and phosphorylation of histones impact gene expression and regulation. However, our increased understanding of RNA modifications and their importance in cellular processes has led to a rise in epitranscriptomics research. “Epitranscriptomics brings together the concepts of epigenetics and gene expression,” explained Adrien Leger, PhD, Principal Research Scientist on Modified Bases...
            Yesterday, 07:01 AM
          • seqadmin
            Current Approaches to Protein Sequencing
            by seqadmin


            Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...
            04-04-2024, 04:25 PM

          ad_right_rmr

          Collapse

          News

          Collapse

          Topics Statistics Last Post
          Started by seqadmin, 04-11-2024, 12:08 PM
          0 responses
          39 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 04-10-2024, 10:19 PM
          0 responses
          41 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 04-10-2024, 09:21 AM
          0 responses
          35 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 04-04-2024, 09:00 AM
          0 responses
          55 views
          0 likes
          Last Post seqadmin  
          Working...
          X