Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • mattanswers
    Member
    • Oct 2009
    • 65

    #1

    Cuffdiff output seems inconsistant

    (I am transferring this question from the RNA-Seq Forum (where I have deleted it) to this Forum)

    I have two sets of time series data. Same conditions, just done on different days. With each set, I have separately gone through TopHat, Cufflinks, Cuffmerge, and Cuffdiff.

    Then I hierarchically clustered the 'significant' ('yes' in the significant column) results and found a small but appreciable subset of genes that are present at one time point (say 30min) in one set, but absent in the other set at the same time point.

    At a closer look, when the gene is significant it is found only once in the gene.exps table output of Cuffdiff, but in the same time point of the other set where it is not significant the gene appears multiple times, each time with an equivalent locus but different log2-fold change values. Also, at least one of the log2-fold change values is very close to the log2-fold change value found for the significant gene in the other set.

    My feeling is that if Cuffdiff did not divide up the gene (multiple entries) it would be significant in that set as well.

    Does anyone have an explanation for why the gene would have multiple entries in one set, but only one entry in other another otherwise equivalent experiment ?
  • mattanswers
    Member
    • Oct 2009
    • 65

    #2
    Some info to clarify the above question

    Let me add, that I realize the difficulties of 'significant' genes when you do not have duplicates.

    The purpose of my analysis is to get an idea of the consistency of results between the two otherwise identical experiments. In other words to check the consistency of the 'bench' experiments.

    The question addressing genes being listed multiple times in the output in one experiment, and only once in the other experiment remains.

    Comment

    Latest Articles

    Collapse

    • SEQadmin2
      How Immunogenomics Decodes Immunity’s Genetic Blueprint
      by SEQadmin2




      The immune system’s power comes from its genetic diversity, allowing myriad threats to be neutralized through first recognizing foreign antigens. That diversity is also what makes the immune system so difficult to study. Recent advances in sequencing technology and computational biology, however, are giving researchers new tools to understand immune responses and immune-related diseases in greater detail.

      This convergence of genetics, immunology, and computation...
      Yesterday, 05:41 AM
    • SEQadmin2
      Beyond CRISPR/Cas9: Understand, Choose, and Use the Right Genome Editing Tool
      by SEQadmin2



      CRISPR/Cas9 sparked the gene editing revolution for both research and therapeutics.1 But this system still showed severe issues that limited its applications. The most prominent were the heavy reliance on PAM sequences, delivery limitations, double-stranded breaks that prompt unintended edits and cell death, and editing inefficiency (both in targeting and in knock-in reliability).

      Despite this, “CRISPR helped turn genome editing from a specialized technique into
      ...
      07-31-2026, 11:01 AM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, 08-24-2026, 10:32 AM
    0 responses
    42 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 08-20-2026, 11:17 AM
    0 responses
    48 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 08-18-2026, 10:05 AM
    0 responses
    55 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 08-13-2026, 12:22 PM
    0 responses
    50 views
    0 reactions
    Last Post SEQadmin2  
    Working...