Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • kmcarr
    Senior Member
    • May 2008
    • 1181

    #1

    Errors in cuffdiff genes.fpkm_tracking file

    I have an mRNA-Seq experiment with a number of samples. After running them through tophat and cuffcompare I then proceeded to run the data through cuffdiff. I wasn't particularly interested in any specific differential expression testing, I just wanted to re-estimate gene level relative expression. I ran cuffdiff providing a curated combined.gtf generated by cuffcompare and four accepted_hits.sam files. According to the cufflinks manual the genes.fpkm_tracking file should contain 4 sets of qX_FPKM, qX_conf_lo and qX_conf_hi data. I was expecting q0 - q3 which is what I see in the isoforms, tss_group tracking files, but in the genes tracking file the first row (headers) lists 12 sets, q0 - q11. What's more, not all rows (loci) have the same number of data points. Many have 12 sets, consistent with the header row, some have only 4 sets which is the expected number and I've even found some rows with as many as 36 sets of FPKM and conf values.

    I am using version 0.8.2 of cufflinks. This result occurs with both the prebuilt x86_64 binaries and binaries I compiled myself.

    Has anyone else observed this behavior when providing more than two samples to cuffdiff?

    Update:

    I have now observed this behavior when only providing 2 input sam files to cuffdiff. The genes.fpkm_tracking file has q0 - q5 data sets.
    Last edited by kmcarr; 05-27-2010, 09:26 AM. Reason: Added information

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
    ...
    07-31-2026, 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, Yesterday, 07:41 AM
0 responses
9 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 08-03-2026, 10:13 AM
0 responses
25 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-31-2026, 02:55 AM
0 responses
38 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-24-2026, 12:17 PM
0 responses
25 views
0 reactions
Last Post SEQadmin2  
Working...