Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • mparida
    Member
    • Mar 2012
    • 15

    #1

    GO analysis

    Hi All
    I am trying to choose between the following:
    a) using all the genes in my genome as a background for my GO analysis
    or
    b) using only those genes that have at least 1 GO term as a background for my GO analysis

    Option a) gives me more (32) enriched GO terms when compared to a set of differentially expressed genes and enhanced q-values
    option b) gives me less (18) enriched GO terms when compared to a set of differentially expressed genes and relatively higher q-values than option a.

    Any help is appreciated. FYI, I am using GOSEQ for my analysis.
    Last edited by mparida; 11-07-2015, 07:02 AM.
  • N311V
    Member
    • Jul 2013
    • 34

    #2
    Personally I think option a) is easier to interpret.

    Given the genome as a background, there are 32 enriched GO terms in this set of differentially expressed genes.

    If you've applied an expression threshold perhaps the background could be expressed genes.

    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, Today, 10:05 AM
    0 responses
    5 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 08-13-2026, 12:22 PM
    0 responses
    31 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 08-11-2026, 10:35 AM
    0 responses
    24 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 08-06-2026, 07:41 AM
    0 responses
    38 views
    0 reactions
    Last Post SEQadmin2  
    Working...