Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • BGould
    Member
    • May 2010
    • 14

    house-keeping genes in RNA-seq data sets?

    Hi All,
    Does anyone out there know of a good reference or two on the depth of coverage required to cover most transcripts and gauge expression levels in RNA-seq experiments? In particular, can anyone give me an idea of what percentage of sequences in their RNA-seq data sets are from what you would consider house-keeping genes? I have one reference in yeast from Wilhelm and Landry (2009) but I can't seem to find much else.
    many thanks . . .
  • pascal
    Junior Member
    • Mar 2010
    • 9

    #2
    You might wanna take a look at this publication:

    Ramsköld,D. et al. (2009) An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS computational biology, 5, e1000598.

    Comment

    • BGould
      Member
      • May 2010
      • 14

      #3
      Thanks!

      thanks Pascal, this study is just what I was looking for. very comprehensive too. many thanks .

      Comment

      • bioinfosm
        Senior Member
        • Jan 2008
        • 483

        #4
        That's very interesting, ignoring UTR mapped reads to remove the bias in rna-seq data!
        --
        bioinfosm

        Comment

        Latest Articles

        Collapse

        • 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.
          Yesterday, 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
        • SEQadmin2
          From Collection to Sequencing: Why Sample Preparation and Preservation Define Sequencing Data
          by SEQadmin2


          Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.


          The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
          ...
          06-02-2026, 10:05 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by SEQadmin2, 06-30-2026, 05:37 AM
        0 responses
        11 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 06-26-2026, 11:10 AM
        0 responses
        18 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 06-17-2026, 06:09 AM
        0 responses
        52 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 06-09-2026, 11:58 AM
        0 responses
        111 views
        0 reactions
        Last Post SEQadmin2  
        Working...