Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Blocking and using contrasts in voom (limma) (RNAseq)

    I am having trouble making the contrast matrix when I am using library preparation type (e.g. paired-end, single-end) as an addition variable in the model matrix:

    Code:
    Treatment <- factor(targets$Treatment[c(1:8,11:13)], levels=c("T1", "T2", "T3", "T4"))
    Seq <- factor(targets$Sequence[c(1:8,11:13)], level=c("single", "pair"))
    design <- model.matrix(~SeqType + Treatment)
    y <- voom(x, design, plot=TRUE)
    fit <- lmFit(y, design)
    Where SeqType is a factor with a value for each RNAseq sample of either paired or single and Treatment is a factor labeling each sample as one of four treatments.

    The resulting design matrix for the fit object is:
    Code:
    (Intercept) Seqpair Treatment2 Treatment3 Treatment4
          1       1        0          1          0  
          1       1        0          0          1
          1       0        1          0          0 
          1       1        1          0          0
          1       1        0          0          0
          1       0        0          0          1
          1       0        0          1          0
          1       0        0          0          0
          1       1        1          0          0
          1       1        0          1          0
          1       1        0          0          1
    I am unsure of how to construct the contrast matrix to test all pairwise comparisons of treatments.

    I have previously used the makeContrasts command, however, I also previously constructed the design matrix by providing it an intercept (design <- model.matrix(~0 + Treatment)) so constructing the contrasts was done by just giving the column headings of the design matrix to the makeContrasts function:

    Code:
    contrast.matrix <- makeContrasts(T1vsT2 = Treatment1-Treatment2)

Latest Articles

Collapse

  • 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
  • seqadmin
    Strategies for Sequencing Challenging Samples
    by seqadmin


    Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
    03-22-2024, 06:39 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, 04-11-2024, 12:08 PM
0 responses
18 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-10-2024, 10:19 PM
0 responses
22 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-10-2024, 09:21 AM
0 responses
17 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-04-2024, 09:00 AM
0 responses
49 views
0 likes
Last Post seqadmin  
Working...
X