Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • proteomania
    Member
    • Sep 2010
    • 11

    Cufflinks merges adjacent genes

    Hi all,

    I am working on the RNA-Seq of an organism with very short intergenic distance (e.g. 50bp). I am using the TopHat/Cufflinks package for my analysis, and I found out Cufflinks tends to merge adjacent genes as a single trasfrag, when the intergenic distance is short. I wonder whether there's an option to adjust the cutoff for the coverage gap size for the definition of a transfrag.

    Thanks in advance.

    cheers,
    Chung
  • GKM
    Member
    • May 2009
    • 45

    #2
    There's a coverage option for filtering out transcripts with "retained introns" that are assembled due to complete coverage of the intron with reads from pre-spliced mRNAs. However, this isn't going to work in your case as the intergenic regions aren't going to be spanned by junctions and I don't think there is any option that does what you want.

    Genes that are on different strands should be assembled relatively correctly, as there the orientation of the junctions will tell Cufflinks what to do. But for genes in the same orientation, you are out of luck, especially if they are at about the same expression levels.

    What you could do is look at you transcript models and try to find those that have two tandem ORFs, those are likely candidates for merged genes. Also, you could try doing ChIP-Seq for histone marks associated with promoters or preinitiation complex components.

    Comment

    Latest Articles

    Collapse

    • SEQadmin2
      Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
      by SEQadmin2



      Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
      ...
      07-09-2026, 11:10 AM
    • 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...
      07-08-2026, 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

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, 07-13-2026, 10:26 AM
    0 responses
    27 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-09-2026, 10:04 AM
    0 responses
    37 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-08-2026, 10:08 AM
    0 responses
    24 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-07-2026, 11:05 AM
    0 responses
    35 views
    0 reactions
    Last Post SEQadmin2  
    Working...