Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • wetSEQer
    Member
    • Dec 2013
    • 15

    #1

    Can I get read counts by doing this???

    I want to quantify the reads I have from several .bam files from Tophat.

    I used two different annotations(one at a time):
    1: CuffMerge generated GTF file;
    2: UCSC genome annotation
    I made a transcript data base by using Bioconductor package "GenomicFeature" function "makeTranscitpDbFromGFF" or "makeTranscitpDbFromUCSC"

    Then I make a object that store the exon or transcripts information, by using Rsamtools package function "exonsBy" or "transcriptsBy"

    Then I do the overlap between my .bam file and the previous object ("countOverlaps")

    Anyone see any problems by doing what I did?

    I took this as a reference:

    Please let me know what could go wrong with this~

    Thanks a lot!
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    Be careful using countOverlaps:

    Code:
    library(IRanges)
    subject <- IRanges(c(1, 4, 9), c(5, 7, 10))
    query <- IRanges(c(2, 2, 10), c(2, 3, 12))
    #If this were RNAseq data, the output should be 0 0 1
    countOverlaps(query, subject)
    You'll see that the counts would be wrong for RNAseq data. You might just use featureCounts or htseq-counts.

    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
      ...
      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

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by SEQadmin2, Yesterday, 10:35 AM
    0 responses
    9 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 08-06-2026, 07:41 AM
    0 responses
    27 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 08-03-2026, 10:13 AM
    0 responses
    45 views
    0 reactions
    Last Post SEQadmin2  
    Started by SEQadmin2, 07-31-2026, 02:55 AM
    0 responses
    48 views
    0 reactions
    Last Post SEQadmin2  
    Working...