Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • jppichon
    Junior Member
    • Jan 2013
    • 1

    #1

    estimateVarianceFunctions

    Hi,

    I tried to do the analysis of the "example.File" with DESeq 1.10.1.
    The following message appeared:

    Erreur : 'estimateVarianceFunctions' is defunct.
    Use 'estimateDispersions' instead.
    See help("Defunct")

    So I tried to use "estimateDispersions". It seemed to be successful, but after running the "nbinomTest" function all padj value were equal to 1 and resVar weren't calculated.

    Does someone has experimented the same?

    JP
  • Simon Anders
    Senior Member
    • Feb 2010
    • 995

    #2
    Please always use a current version of both the package and the documentation. You seem to be reading an old version of the vignette if it still mentions 'estimateVarianceFunction'.

    As for the p values, you will have to give us much more information on what you are doing before we can make any guesses.

    Comment

    • Baoqing
      Member
      • Jan 2013
      • 24

      #3
      p value is negative

      Hi, Guys

      I probably followed the old version as well. But after the error message, i changed to run:
      cds = estimateDispersions(cds)
      res = nbinomTest(cds, "T", "N") #T, N two treatments, all of my samples are single reads

      When i looked at the results:

      i saw p value is negative in some rows, however, the adjusted p value seems okay. Is it normal, or do i have to specify more parameters?

      Thank you!

      Comment

      • Simon Anders
        Senior Member
        • Feb 2010
        • 995

        #4
        Negative p values are impossible. You must have either uncovered a very subtle bug, or have done something wrong. Post more details if the problem persists.

        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, 08-06-2026, 07:41 AM
        0 responses
        16 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 08-03-2026, 10:13 AM
        0 responses
        31 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 07-31-2026, 02:55 AM
        0 responses
        42 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 07-24-2026, 12:17 PM
        0 responses
        26 views
        0 reactions
        Last Post SEQadmin2  
        Working...