Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • giu.facchetti
    Junior Member
    • Dec 2013
    • 2

    #1

    dispersion from DESeq

    hello,
    I have started working with DESeq for RNASeq data from plants.
    Among the first plots I have got, there is the dispersion (D) vs counts mean (M). This plot is fitted with the curve D=a+b/M (which in a log-log scale is a decreasing curve that reaches a plateau for high value of M, see attachment).
    However, my data show a linear correlation (still in the log-log plot).
    Is my analysis wrong? can I change the fitting expression? why the fitting procedure does not set a=0 which would give a linear relationship between Log(D) and Log(M)?

    thanks!
    Attached Files
  • Wolfgang Huber
    Senior Member
    • Aug 2009
    • 109

    #2
    Dear Giu.facchetti,

    thank you for the feedback. Some suggestions:
    1. The attached jpeg image came out very small (100x115x) making it hard to impossible to read (at least for me).
    2. Such a strange-looking plot may (or may not) be indicative of a data quality problem, e.g. large batch effect or sample-swap. Have you explored that? (The DESeq2 vignette gives some suggestions on how to do that.)
    3. Have you tried the argument fitType = "local" to estimateDispersions?
    4. Since you are just starting, the authors of the package recommend you use DESeq2 now, since it offers many improvements.

    Kind regards
    Wolfgang
    Wolfgang Huber
    EMBL

    Comment

    • giu.facchetti
      Junior Member
      • Dec 2013
      • 2

      #3
      Thank you for the suggestions!
      Unfortunately the option "fit=local" did not improve the fitting (the fitting line was even much curved). Same results with DESeq2.
      At the moment I am doing again the alignment and reads counts, trying to improve the sensitivity and accuracy.

      Comment

      Latest Articles

      Collapse

      • 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
      • SEQadmin2
        Proteomic Platforms: How to Choose the Right Analytical Strategy to Improve Detection and Clinical Applications
        by SEQadmin2


        Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.

        The systematic characterization of the human proteome has
        ...
        07-20-2026, 11:48 AM

      ad_right_rmr

      Collapse

      News

      Collapse

      Topics Statistics Last Post
      Started by SEQadmin2, 08-13-2026, 12:22 PM
      0 responses
      28 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 08-11-2026, 10:35 AM
      0 responses
      23 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 08-06-2026, 07:41 AM
      0 responses
      37 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 08-03-2026, 10:13 AM
      0 responses
      51 views
      0 reactions
      Last Post SEQadmin2  
      Working...