Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • htseq-count overlap modes

    Hi! I'm using htseq-count to count reads from my RNASeq experiment mapping to genes. I have an alignment file where all reads are mapped to the genome, and now I am just counting reads for each gene. It seems to work fine, but I'm trying to understand a specific detail about how it works. Basically, it has 3 overlap modes and I am using the 'union':



    This is the documentation: http://www-huber.embl.de/users/ander...doc/count.html

    I'm wondering if anyone knows to what extend does it count partially mapped reads (2nd row from the figure), i.e. by how much should the read overlap for it to be counted?

    The figure implies it counts partial overlaps too, but does not specify what exactly the minimum overlap needs to be. I'm not finding this information in the documentation.

    Thanks!

  • #2
    A one base overlap counts as an overlap.

    Comment


    • #3
      Thanks, looks like you're right. I've come to the same conclusion just now inspecting their python source code. How's that meaningful?

      I guess if there's a very small overlap (extreme case: just overlap 'A' from 'ATG' at beginning) then it's likely overlapping multiple genes, hence it's classified as 'ambiguous' and not counted?

      Comment


      • #4
        Yes, but that depends on how dense the genes are in your genome, and how long your reads are

        Comment


        • #5
          Originally posted by is007 View Post
          Thanks, looks like you're right. I've come to the same conclusion just now inspecting their python source code. How's that meaningful?
          There's no real meaning there other than how sets are dealt with.

          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
          12 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 04-10-2024, 10:19 PM
          0 responses
          17 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 04-10-2024, 09:21 AM
          0 responses
          14 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 04-04-2024, 09:00 AM
          0 responses
          43 views
          0 likes
          Last Post seqadmin  
          Working...
          X