Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • EdgeR -- normalisation and paired test.

    Hi I am runing EdgeR to make an exact t-test (Iwould like to do a pairwise cmparaison but I am still not sure about that).
    So here is to way I can compare time 0 versus time 8 for the positive responder on the experiment.
    In one case I am normalising with all my data, then I filter all those who respond positively
    In the other case I just take the positive responder for normalisation.

    Of course the first case seems better but I would like to have your comments ...
    Question : Would you take some data from another experiment to help data normalisation ?
    Question : Would you give me a tips to use subject number to pair my sample over time ?

    Code:
    miRNA=read.table("merged_filtered_data.csv", header=TRUE,row.names=1)
    roundmiRNA=round(miRNA)
    
    info=read.table("samples_infos.csv", header=TRUE,row.names=1)
    miRNAdesign=data.frame(row.names = colnames(info),
      week=t(info)[,"week"],
      subject=t(info)[,"sub"],
      response=t(info)[,"MARSD"]
    )
    
    is_responder=miRNAdesign$response==1
    
    #first way to do it
    
    y <- DGEList(counts=roundmiRNA,group=miRNAdesign$week)
    y <- calcNormFactors(y)
    y <- estimateCommonDisp(y, verbose=TRUE)
    y <- estimateTagwiseDisp(y,trend="none")
    et <- exactTest(y[,is_responder])
    topTags(et)
    
    
    #second way to do it
    
    y <- DGEList(counts=roundmiRNA[,is_responder],group=miRNAdesign$week[is_responder])
    y <- calcNormFactors(y)
    y <- estimateCommonDisp(y, verbose=TRUE)
    y <- estimateTagwiseDisp(y,trend="none")
    et <- exactTest(y)
    topTags(et)

  • #2
    You can download data of other experiments from SRA.

    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, Today, 08:47 AM
    0 responses
    12 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 04-11-2024, 12:08 PM
    0 responses
    60 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 04-10-2024, 10:19 PM
    0 responses
    59 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 04-10-2024, 09:21 AM
    0 responses
    54 views
    0 likes
    Last Post seqadmin  
    Working...
    X