Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • aritakum
    Junior Member
    • Jun 2009
    • 5

    ChIPSeq: Unusual narrow peaks

    HI,
    I am looking at some ChIPSeq data that is rather unusual. The forward and reverse reads form deep thin stacks. Their width is mostly just above the read length of 75 bp. The 'peaks' (pseudo-peaks?) are distributed well across the mouse genome. Have any of you see this? What could be the reason? This experiment is investigating transcription factor binding ....


    Thanks!
    Jarus
  • ffinkernagel
    Senior Member
    • Oct 2009
    • 110

    #2
    Hm. Sounds to me like a very low complexity library - I have seen one or two of those, but can only speculate about the reason.
    Perhaps very low amounts of input dna with too many PCR cycles?

    Comment

    • ETHANol
      Senior Member
      • Feb 2010
      • 308

      #3
      Sounds like a low complexity issue but it would be helpful if you posted some images of what the data looks like.
      --------------
      Ethan

      Comment

      • aritakum
        Junior Member
        • Jun 2009
        • 5

        #4
        RE: ChIPSeq: Unusual narrow peaks

        Attached is a screen shot of what I typically see through out the genome
        Attached Files

        Comment

        • steinmann
          Member
          • Feb 2010
          • 64

          #5
          Yes, thats what PCR artifacts from low complexity libraries look like.

          Comment

          • aritakum
            Junior Member
            • Jun 2009
            • 5

            #6
            Thank you all. I think its time to get back to re-doing experiment. I guess, Data analysis-wise there is not much to do...

            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.
              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, 07-02-2026, 11:08 AM
            0 responses
            11 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 06-30-2026, 05:37 AM
            0 responses
            13 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 06-26-2026, 11:10 AM
            0 responses
            20 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 06-17-2026, 06:09 AM
            0 responses
            54 views
            0 reactions
            Last Post SEQadmin2  
            Working...