Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • DESeq on "small genome" data

    Hi guys,
    I'm interested in your opinion, whether it is a good idea to use DESeq application for DE in an experiment where number of transcripts present in the sequencing mixture would be extremely small.
    I'm dealing with RNA-seq sequencing data for 50 amplicons, that have been tested for differential expression. This is some kind of test for tissue-specific expression of biomarkers.
    On one hand, DESeq may be more resistant to variance inequality in compared series than lmFit, on the other hand - is it right to estimate variance-mean dependance using just 50 points???
    limma's lmFit-eBayes worked just fine last time with similar data, but this time the variance in some amplicons is just dragging pVals towards 1.
    PS. study of 50 amplicons behaviour via RNA-seq was NOT my idea, I'm just dealing with the output.

    Thanks,
    Elizabeth

  • #2
    You are right, estimating variance-mean relation from just 50 data points is indeed not such a great idea. In our new DESeq2 package, we now offer the new option fitType="mean" for estimateDispersions which just fits a single mean dispersion and shrinks the gene-wise estimates towards it. This might work well. However, if the variance it too high for limma, DESeq2 will also not see more, I suppose.

    Do you mean that the amplicons with high variance have high p values? That would be correct. Or do you mean that the high-variance amplicons pull up the variance estimates for the other amplicons? Then you may want to use some independent filtering beforehands.

    Comment

    Latest Articles

    Collapse

    • seqadmin
      Best Practices for Single-Cell Sequencing Analysis
      by seqadmin



      While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
      06-06-2024, 07:15 AM
    • seqadmin
      Latest Developments in Precision Medicine
      by seqadmin



      Technological advances have led to drastic improvements in the field of precision medicine, enabling more personalized approaches to treatment. This article explores four leading groups that are overcoming many of the challenges of genomic profiling and precision medicine through their innovative platforms and technologies.

      Somatic Genomics
      “We have such a tremendous amount of genetic diversity that exists within each of us, and not just between us as individuals,”...
      05-24-2024, 01:16 PM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by seqadmin, Today, 07:23 AM
    0 responses
    8 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 06-17-2024, 06:54 AM
    0 responses
    11 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 06-14-2024, 07:24 AM
    0 responses
    24 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 06-13-2024, 08:58 AM
    0 responses
    18 views
    0 likes
    Last Post seqadmin  
    Working...
    X