Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • abh
    Member
    • Aug 2012
    • 13

    #1

    cufflinks multiple FPKM values for same location

    Hi,

    i have run cufflinks for my Bam files to look after the FPKM values and i got the output.

    later i took the output transcripts.gtf and converted into bedgraph file to view in UCSC genome browser,but i got different fpkm values for same location

    what should i do with them?should i sum up?is there any script or any tool that i can use it(just for saving the time)

    here is the sample bedgraph file

    track type=bedGraph name=s6 visibility=full color=255,0,0
    chr1 11874 12227 0.0000000000
    chr1 11874 12227 0.0286938296
    chr1 11874 12227 0.1072298182
    chr1 11874 14409 0.0000000000
    chr1 11874 14409 0.0286938296
    chr1 11874 14409 0.1072298182
    chr1 12595 12721 0.0000000000
    chr1 12613 12721 0.1072298182
    chr1 12646 12697 0.0286938296

    Thank you
    Last edited by abh; 04-08-2013, 10:48 AM.
  • glados
    Member
    • Mar 2012
    • 59

    #2
    I get the same problem. I get several gene_ids with identical coordinates. It's so frustrating. How come cufflinks don't understand it is only one gene when they have identical coordinates? (using the latest cufflinks 2.1.1)

    Comment

    • SrCardgage
      my other car is a limozeen
      • Feb 2012
      • 23

      #3
      different transcripts for the same gene

      It's not so much cufflink's problem as it is the records in the gtf file. Like me, you probably grabbed a publicly available version of the gtf file. This file has many TRANSCRIPTS for the same gene. These usually represent different isoforms of the gene. For some analyses, it is important to know the distinction.

      My analysis did not need to know this, so I wrote a python script to choose only one transcript. Here is my script. It is VERY kludgy, but it works.

      Please note that I had to change the file extension to ".txt" from ".py" in order to include it in this post.

      The logic behind isolating down to a single transcript is near the top of the file, in the comments. If you have problems understanding this, please DO NOT pm me. Post to this thread and I will respond when I find the time (probably a few days).

      And please, no comments on my coding conventions; positive or negative.
      Attached Files

      Comment

      Latest Articles

      Collapse

      • SEQadmin2
        Beyond CRISPR/Cas9: Understand, Choose, and Use the Right Genome Editing Tool
        by SEQadmin2



        CRISPR/Cas9 sparked the gene editing revolution for both research and therapeutics.1 But this system still showed severe issues that limited its applications. The most prominent were the heavy reliance on PAM sequences, delivery limitations, double-stranded breaks that prompt unintended edits and cell death, and editing inefficiency (both in targeting and in knock-in reliability).

        Despite this, “CRISPR helped turn genome editing from a specialized technique into
        ...
        Today, 11:01 AM
      • SEQadmin2
        Proteomic Platforms: How to Choose the Right Analytical Strategy to Improve Detection and Clinical Applications
        by SEQadmin2


        Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.

        The systematic characterization of the human proteome has
        ...
        07-20-2026, 11:48 AM
      • 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

      ad_right_rmr

      Collapse

      News

      Collapse

      Topics Statistics Last Post
      Started by SEQadmin2, Today, 02:55 AM
      0 responses
      7 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 07-24-2026, 12:17 PM
      0 responses
      11 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 07-23-2026, 11:41 AM
      0 responses
      12 views
      0 reactions
      Last Post SEQadmin2  
      Started by SEQadmin2, 07-20-2026, 11:10 AM
      0 responses
      24 views
      0 reactions
      Last Post SEQadmin2  
      Working...