Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • How to use DESeq with non Integer values from mirdeep2

    Hi,

    I've recently started using mirdeep2 for miRNAseq data and would like to do a DE analysis between two conditions.

    The normalised miRNA expressions were given in an output file by mirdeep2 called "miRNAs_expressed_all_samples_now.csv" which contained colums like this:

    #miRNA read_count precursor total seq seq(norm)
    mmu-let-7a-1-3p 571.00 mmu-let-7a-1 571.00 571.00 74.79
    mmu-let-7a-5p 38731.00 mmu-let-7a-1 38731.00 38731.00 5073.08

    The colum with my normalised scores (seq(norm)) has non integer values which I have been unable to use with DESeq to perform a DE analysis.

    I was given the following error when i tried to attatch my conditions to the counts table.
    > cds<-newCountDataSet(countsTable, conds)
    Error in newCountDataSet(countsTable, conds) :
    The countData is not integer.

    Has anyone come across this before? Should i convert my seq(norm) colum to integer values or is there a way to force DESeq to accept non integer values.

    Any help or advice you can give would be much appriciate.

  • #2
    When I went through the mirdeep2 to DESeq, I just used the raw counts as output by mirdeep2 and not the mideep2 normalized counts. DESeq will normalize for you anyway.

    Comment


    • #3
      Excellent! That worked like a charm.

      Cheers

      Comment


      • #4
        Originally posted by Wallysb01 View Post
        When I went through the mirdeep2 to DESeq, I just used the raw counts as output by mirdeep2 and not the mideep2 normalized counts. DESeq will normalize for you anyway.
        Hi, Wallysb01, if I use -W in quantifier.pl options which you mentioned in another thread then the raw counts will have non-integer numbers. How to deal with this situation? Is that appropriate to use function 'round' in R to convert these numbers to integer?
        Thanks~

        Comment

        Latest Articles

        Collapse

        • seqadmin
          Genetic Variation in Immunogenetics and Antibody Diversity
          by seqadmin



          The field of immunogenetics explores how genetic variations influence immune responses and susceptibility to disease. In a recent SEQanswers webinar, Oscar Rodriguez, Ph.D., Postdoctoral Researcher at the University of Louisville, and Ruben Martínez Barricarte, Ph.D., Assistant Professor of Medicine at Vanderbilt University, shared recent advancements in immunogenetics. This article discusses their research on genetic variation in antibody loci, antibody production processes,...
          11-06-2024, 07:24 PM
        • seqadmin
          Choosing Between NGS and qPCR
          by seqadmin



          Next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR) are essential techniques for investigating the genome, transcriptome, and epigenome. In many cases, choosing the appropriate technique is straightforward, but in others, it can be more challenging to determine the most effective option. A simple distinction is that smaller, more focused projects are typically better suited for qPCR, while larger, more complex datasets benefit from NGS. However,...
          10-18-2024, 07:11 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by seqadmin, Today, 11:09 AM
        0 responses
        22 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, Today, 06:13 AM
        0 responses
        20 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 11-01-2024, 06:09 AM
        0 responses
        30 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 10-30-2024, 05:31 AM
        0 responses
        21 views
        0 likes
        Last Post seqadmin  
        Working...
        X