Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • How to measure miRNA expression from Illumina libraries

    I have a 51 single-end reads generated with MiSeq using NEBNext Multiplex Oligos for Illumina.

    The data is obtained from from blood serum miRNA.

    The sample sheet looks like this:

    Code:
    IEMFileVersion,4
    Investigator Name,FB
    Experiment Name,WT10104
    Date,11/27/2013
    Workflow,GenerateFASTQ
    Application,FASTQ Only
    Assay,TruSeq Small RNA
    Description,
    Chemistry,Default
    
    [Reads]
    51
    
    [Settings]
    ReverseComplement,0
    
    [Data]
    Sample_ID,Sample_Name,Sample_Plate,Sample_Well,I7_Index_ID,index,Sample_Project,Description
    HS130333-1,,,,RPI3,TTAGGC,,
    HS130333-2,,,,RPI4,TGACCA,,
    HS130333-3,,,,RPI5,ACAGTG,,
    So it contain 3 files:
    Code:
    HS130333-1.fastq
    HS130333-2.fastq
    HS130333-3.fastq
    My question is, if I want to measure the miRNA expression,
    should I combine all the 3 files above, then map them before computing the expression?

    OR map each of the above 3 files individually and then average the expression?

  • #2
    I suggest you to map individually, because you get more statistical power for further analysis.

    Comment


    • #3
      Hi foolishbrat,

      I agree with TiborNagy that the best option is to map them individually and the compute the miRNA expression separately.

      On the other hand, I also suggest you to apply some type of normalization before going further on the analysis of miRNA expression. Here) you'll find a survey of normalization methods for small RNA-Seq data.

      Hope this helps

      Comment


      • #4
        Thanks a million both.

        Comment

        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
        24 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-10-2024, 10:19 PM
        0 responses
        25 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-10-2024, 09:21 AM
        0 responses
        22 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-04-2024, 09:00 AM
        0 responses
        52 views
        0 likes
        Last Post seqadmin  
        Working...
        X