Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • How to deal with samples partially without replicates in DESeq?

    I have four groups of samples, 2 groups with replicates and 2 groups without. The data frame is like this:
    expt_design<-data.frame(row.name=colnames(colon)
    + condition=c("GF","SPF","9343","9343","SPT","SPT"))
    Error: unexpected symbol in:
    "expt_design<-data.frame(row.name=colnames(colon)
    condition"
    > expt_design<-data.frame(row.names=colnames(colon),
    + condition=c("GF","SPF","9343","9343","SPT","SPT"))
    > expt_design
    condition
    GF GF
    SPF SPF
    X9343.1 9343
    X9343.2 9343
    SPT.1 SPT
    SPT.2 SPT
    > conditions=expt_design$condition
    > conditions
    [1] GF SPF 9343 9343 SPT SPT
    Levels: 9343 GF SPF SPT

    When I tried to run it gave me this error message:
    >cds=estimateDispersions(cds)
    Error in .local(object, ...) :
    None of your conditions is replicated. Use method='blind' to estimate across conditions, or 'pooled-CR', if you have crossed factors.

    Plz help me to identify the problem and tell me how to deal with partially replicated samples

  • #2
    Did you read the error message, the fix is contained within it. Also, you should read the DESeq tutorial.

    Comment


    • #3
      You might have confused DESeq by passing your "condition" data as a data.frame rather than as a factor. Try again using

      cds <- newCountDataSet( countTable, exptDesign$condition)

      And consider switching to DESeq2. It not only has improved power; we have also improved the interface to avoid problems like this one.

      Comment

      Latest Articles

      Collapse

      • seqadmin
        Essential Discoveries and Tools in Epitranscriptomics
        by seqadmin




        The field of epigenetics has traditionally concentrated more on DNA and how changes like methylation and phosphorylation of histones impact gene expression and regulation. However, our increased understanding of RNA modifications and their importance in cellular processes has led to a rise in epitranscriptomics research. “Epitranscriptomics brings together the concepts of epigenetics and gene expression,” explained Adrien Leger, PhD, Principal Research Scientist...
        04-22-2024, 07:01 AM
      • seqadmin
        Current Approaches to Protein Sequencing
        by seqadmin


        Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...
        04-04-2024, 04:25 PM

      ad_right_rmr

      Collapse

      News

      Collapse

      Topics Statistics Last Post
      Started by seqadmin, Yesterday, 11:49 AM
      0 responses
      15 views
      0 likes
      Last Post seqadmin  
      Started by seqadmin, 04-24-2024, 08:47 AM
      0 responses
      16 views
      0 likes
      Last Post seqadmin  
      Started by seqadmin, 04-11-2024, 12:08 PM
      0 responses
      61 views
      0 likes
      Last Post seqadmin  
      Started by seqadmin, 04-10-2024, 10:19 PM
      0 responses
      60 views
      0 likes
      Last Post seqadmin  
      Working...
      X