Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • ea11
    Member
    • Jun 2015
    • 36

    #1

    Design matrix for edgeR help

    Hi,

    I am attempting to create a design matrix in edgeR to determine differentially expressed genes, but I am unsure on the notation to use as I am relatively new to R and not a statistician in any way.

    Basically, the experimental design is as follows:

    We have two treatments (A and B), each treatment had two cages and in each cage, there were 3 mice. Therefore in total, we have 6 mice for each treatment, coming from 2 cages for each treatment (total of 4 cages). We are not interested in the effect of the different cages, but are interested in differentially expressed genes between the 2 treatments (A and B).

    So what I was wondering is what the design matrix would be taking into account that cage is nested in treatment. Would it be one of the following or something completely different:

    PHP Code:
    design <- model.matrix(~cage/treatment)

    design <- model.matrix(~treatment*cage)

    design <- model.matrix(~cage %intreatment
    Thanks for any help

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
  • SEQadmin2
    Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
    by SEQadmin2



    Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
    ...
    07-09-2026, 11:10 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by SEQadmin2, Yesterday, 10:13 AM
0 responses
14 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-31-2026, 02:55 AM
0 responses
29 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-24-2026, 12:17 PM
0 responses
22 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-23-2026, 11:41 AM
0 responses
21 views
0 reactions
Last Post SEQadmin2  
Working...