Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • ahodgins
    Junior Member
    • Jan 2010
    • 4

    Tag-Seq vs RNA-Seq

    Hi all,

    Does anyone know of any papers directly comparing RNA-Seq to Tag-Seq results? (Ideally, DpnII digital expression count data in yeast, but I'd take what I could get.)

    The situation: We have some old data using DpnII tag profiling to compare our homemade microarrays with Illumina digital gene expression counts. Its a rich dataset using two different priming methods to compare across platforms (microarrays vs digital Tag-Seq). Now, I have an additional RNA-seq dataset prepared with random fragmentation, not restriction endonuclease-generated tags. I'd love to be able to use the work we've already done to robustly compare my new RNA-Seq data to the same microarrays, but I'm aware that the Tag-Seq results are not directly comparable to the RNA-Seq results. What I'm wondering is if I can reasonably estimate the relationship by counting DpnII cut sites and scaling RNA-Seq counts by gene length or whether there are some further effects I'm missing.

    Thanks for any insight you can offer!

    Andrea
  • DPresto
    Junior Member
    • Apr 2020
    • 1

    #2
    Hi Andrea,

    Apologies for resurrecting such an old thread, but I wanted to know if you ever got a satisfactory answer to this question, as I have the same one.

    Best,

    -Devin

    Comment

    Latest Articles

    Collapse

    • SEQadmin2
      Cancer Drug Resistance: The Lingering Barrier to Rising Survival
      by SEQadmin2



      Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

      There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
      Today, 05:17 AM
    • GATTACAT
      Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by GATTACAT
      Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
      07-01-2026, 11:43 AM
    • SEQadmin2
      Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by SEQadmin2


      I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

      Here are nine questions we think about, in roughly the order they matter, before...
      06-18-2026, 07:11 AM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, Yesterday, 11:05 AM
    0 responses
    7 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-02-2026, 11:08 AM
    0 responses
    28 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 06-30-2026, 05:37 AM
    0 responses
    28 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 06-26-2026, 11:10 AM
    0 responses
    27 views
    0 reactions
    Last Post SEQadmin2  
    Working...